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-portal.org The Digital Divide: The Internet and Social Inequality in International Perspective
http://www.diva-portal.org
This is the published version of a chapter published in The Digital Divide: The Internet and Social
Inequality in International Perspective.
Citation for the original published chapter:
Meinrath, S., Losey, J., Lennett, B. (2013)
Afterword. Internet Freedom, Nuanced Digital Divide, and the Internet Craftsman.
In: Massimo Ragnedda and Glenn W. Muschert (ed.), The Digital Divide: The Internet and Social
Inequality in International Perspective (pp. 309-316). London: Routledge
Routledge advances in sociology
N.B. When citing this work, cite the original published chapter.
Permanent link to this version:
http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-100423
The Digital Divide
This book provides an in-depth comparative analysis of inequality and the
stratification of the digital sphere.
Grounded in classical sociological theories of inequality, as well as empirical
evidence, this book defines “the digital divide” as the unequal access and utility of
internet communications technologies and explores how it has the potential to
replicate existing social inequalities, as well as create new forms of stratification.
The Digital Divide examines how various demographic and socio-economic factors
including income, education, age and gender, as well as infrastructure, products
and services affect how the internet is used and accessed. Comprised of six parts,
the first section examines theories of the digital divide, and then looks in turn at:
•
•
•
•
•
Highly developed nations and regions (including the USA, the EU and
Japan);
Emerging large powers (Brazil, Russia, India, China);
Eastern European countries (Estonia, Romania, Serbia);
Arab and Middle Eastern nations (Egypt, Iran, Israel);
Under-studied areas (East and Central Asia, Latin America, and sub-Saharan
Africa).
Providing an interwoven analysis of the international inequalities in internet
usage and access, this important work offers a comprehensive approach to
studying the digital divide around the globe. It is an important resource for
academics and students in sociology, social policy, communication studies, media
studies and all those interested in the questions and issues around social
inequality.
Massimo Ragnedda teaches Mass Communications at Northumbria University,
UK. Previously he was an affiliated visitor at the Department of Sociology,
University of Cambridge, UK and in 2011 he was Academic Visiting at the Oxford
Internet Institute, University of Oxford, UK.
Glenn W. Muschert is Associate Professor in the Sociology, Criminology, and
Social Justice Studies Programs at Miami University, USA.
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The Digital Divide_BOOK.indb 2
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The Digital Divide
The internet and social inequality in
international perspective
Edited by
Massimo Ragnedda and
Glenn W. Muschert
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First published 2013
by Routledge
2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
Simultaneously published in the USA and Canada
by Routledge
711 Third Avenue, New York, NY 10017
Routledge is an imprint of the Taylor & Francis Group, an informa business
© 2013 selection and editorial material, Massimo Ragnedda and
Glenn W. Muschert; individual chapters, the contributors
The right of the editors to be identified as the authors of the
editorial material, and of the authors for their individual chapters,
has been asserted in accordance with sections 77 and 78 of the
Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or
reproduced or utilised in any form or by any electronic, mechanical,
or other means, now known or hereafter invented, including
photocopying and recording, or in any information storage or
retrieval system, without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks or
registered trademarks, and are used only for identification and
explanation without intent to infringe.
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging in Publication Data
The digital divide : the Internet and social inequality in
international perspective / edited by Massimo Ragnedda and
Glenn W. Muschert.
pages cm. -- (Routledge advances in sociology ; 73)
1. Digital divide. 2. Information society. 3. Equality. I. Ragnedda,
Massimo, 1976- II. Muschert, Glenn W.
HM851.D52444 2013
302.23'1--dc23
2012046956
ISBN: 978-0-415-52544-2 (hbk)
ISBN: 978-0-203-06976-9 (ebk)
Typeset in Baskerville
by Saxon Graphics Ltd, Derby
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Contents
Author biographiesviii
Prefacexviii
Introduction
1
M assimo R agnedda and Glenn W. Muschert
Section 1
Theories of the digital divide15
1 The reproduction and reconfiguration of inequality:
Differentiation and class, status and power in the
dynamics of digital divides
Bridgette W essels
2 A theory of the digital divide
17
29
Jan A.G.M. van Dijk
Section 2
Highly developed nations and regions53
3 The digital divide in Europe
Nicole Zillien and Mirko M arr
4 The Internet and social inequalities in the U.S.
67
James W itte, M arissa K iss and R andy Lynn
5 Missing in the midst of abundance: The case of
broadband adoption in Japan
55
85
Mito A kiyoshi, Motohiro Tsuchiya and Takako Sano
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vi Contents
Section 3
Rapidly developing large nations – the BRIC nations105
6 The digital divide in Brazil: Conceptual, research and
policy challenges
7 Digitalizing Russia: The uneven pace of progress toward
ICT equality
107
Bernardo Sorj
118
Inna F. Deviatko
8 The digital divide in India: Inferences from the
information and communication technology
workforce134
P. V igneswara Ilavarasan
9 The digital divide in China, Hong Kong and Taiwan:
The barriers of first order and second order digital
divide147
Shu-Fen Tseng and Y u- Ching You
Section 4
Eastern Europe163
10 The Internet and digital divide in South Eastern
Europe: Connectivity does not end the digital divide,
skills do
11 Closing the gap, are we there yet?: Reflections on the
persistence of second-level digital divide among
adolescents in Central and Eastern Europe
177
Monica Barbovschi and Bianca Bale a
12 Behind the slogan of “e-State”: Digital stratification
in Estonia
165
Danica R adovanovi ć
191
V eronika K almus, K airi Talves and
Pille Pruulmann-V engerfeldt
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Contents vii
Section 5
The Middle East region205
13 Digitally divided we stand: The contribution of digital
media to the Arab Spring
14 Explaining digital inequalities in Israel: Juxtaposing
the conflict and cultural perspectives
207
David M. Faris
220
Gustavo Mesch, Ilan Talmud and Tanya Kolobov
15 An analysis of the second-level digital divide in Iran:
A case study of University of Tehran undergraduate
students235
H amid A bdollahyan, Mehdi Semati and Mohammad A hmadi
Section 6
Under-studied countries and regions249
16 The digital divide in the Latin American context
17 The Central Asian digital divide
268
Barney Warf
18 The double digital divide and social inequality in Asia:
Comparative research on Internet cafes in Taiwan,
Singapore, Thailand, and the Philippines
251
Daniela Trucco
283
Tomohisa Hirata
19 Dimensions of the mobile divide in Niger
295
Gado A lzouma
Afterword: Internet freedom, nuanced digital divides, and
the Internet craftsman307
Sascha D. Meinrath, James Losey and Benjamin Lennett
Index314
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Author biographies
Hamid Abdollahyanis an Associate Professor of Communication at the
Department of Communication, Faculty of Social Sciences, University
of Tehran, Iran. His research interests include new media and cultural
differences, media and the public sphere, cultural studies and the
generation gap, consumer culture and the automobile industry,
research methods in communications studies, comparative dimensions
of sociology, communication and history, historical sociology, social
networking, human-computer interaction, the Internet world and its
problematic for science. His writing includes the books Conceptualization
of reality in historical sociology: Narrating absentee-landlordism in Iran (2004)
and Comparative Perspectives in Sociology, Anthropology and Communication
(2008). He has also published a number of articles in journals such as
Alternate Routes, Critique; Critical Middle Eastern Studies, WeltTrends, Asian
Journal of Social Sciences, Journal of Media and Religion, Iranian Social
Science Letter, Communication and Culture, Global Media Journal, and in
Women’s Studies. He has done extensive research on the generation gap
in Iran and his latest research reports came out in spring 2005, spring
2006 and spring 2007. He is currently working on theoretical
dimensions of the Internet and pathology. He has also worked on
comparative aspects of university professors’ work load versus salaries.
Mohammad Ahmadiis a PhD student in the Department of Media and
Communication Studies at the University of Tehran. His research
interests include areas of digital literacy, digital divide and new media.
He has published articles in these fields in scholarly journals such as
Amity Journal of Media and Communication Studies.
Mito Akiyoshiis a professor in the Department of Sociology at Senshu
University. Professor Akiyoshi has written and lectured widely on social
implications of information and communication technologies. Her
publications include “The diffusion of mobile Internet in Japan” (with
Hiroshi Ono, Information Society 24(5)) and “Les Japonais en ligne: Le
prisme des générations et des classes sociales” (Hermès 55).
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Author biographies ix
Gado Alzoumais Associate Professor of Anthropology at the American
University of Nigeria (AUN), Yola. He did his undergraduate and
graduate studies in France (Bordeaux and Strasbourg). He also is the
holder of a PhD in Anthropology from Southern Illinois University,
Carbondale, USA. Before joining AUN, he was Assistant Professor at
the Department of Sociology, Abdou Moumouni University, Niamey,
Niger. His research and publications focus on information and
communication technologies for development. He is the author of
several papers in refereed journals. Contact: American University of
Nigeria , Lamido Zubairu Way, Yola By-Pass, Yola, Adamawa, Nigeria
Email: [email protected]
Bianca Balea(PhD) got her doctoral degree in November 2012 with a
thesis on “Digital inequalities among children” at the Faculty of
Sociology and Social Work, Babeș-Bolyai University, Cluj-Napoca,
Romania. Since September 2011 she has been a member of the EU Kids
Online project with the Romanian team. Her current research interests
are new media and society, social and digital inequalities, and children’s
use of new digital technologies.
Monica Barbovschiis a postdoctoral fellow at the Institute for Research of
Children, Youth and Family (Masaryk University, Brno, Czech Republic)
and an associated researcher at the Institute of Sociology, Romanian
Academy. Her research interests are at the intersection between
sociology of childhood and children’s rights, and are currently
materialised into projects related to children’s Internet and mobile
Internet use. She is the contact person for Romania in the EU Kids
Online Project (EC Safer Internet Programme).
Inna F. Deviatkois Professor of Sociology at the National Research
University Higher School of Economics where she is Head of the
Department of Analysis of Social Institutions. She has also been the
editor-in-chief of Sociology: Methodology, Methods, Mathematical Modeling,
an academic peer-reviewed journal since 2010. Her current research
interests include classical and contemporary sociological theory and
sociological methodology (including online research methods). Her
main books are Diagnostic procedure in sociology: An essay on history and
theory (1993); Models of explanation and logic of sociological research (1996);
Sociological theories of agency and practical rationality (2003); and Methods of
sociological research, 6th Edition (2010).
David M. Farisis Assistant Professor of Political Science and Director of
International Studies at Roosevelt University. He is the author of Dissent
and revolution in a digital age: Social media, blogging and activism in Egypt
(IB Tauris and Co., 2012). His work has appeared in Arab Media &
Society, Middle East Policy, Politique Etrangere, as well as in The Routledge
participatory cultures handbook. Faris also serves as Strategy Group Advisor
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x Author biographies
for the Meta-Activism Project (MAP), which seeks to build foundational
knowledge about digital activism. He has also written for the Christian
Science Monitor, NPR.org, The Daily News Egypt, The Philadelphia City Paper,
and Insights on Law and Society.
Tomohisa Hiratais a postdoctoral fellow of JSPS in Kyoto University. He is a
member of the External Committee of the Society of Socio-Informatics
and was previously a member of the Research Committee of the Japan
Society for Socio-Information Studies. His recent research is to clarify the
relation between Internet uses in Asian countries and their cultural
backgrounds by focusing on Internet cafes from the perspectives of
theoretical sociology, anthropology, and human geography.
Daniela Trucco Horwitzis a sociologist from the Pontificia Universidad
Católica de Chile with a Master’s Degree in Public Policy and Business
Administration from the University of Maryland, U.S.A. Her
professional experience has concentrated on research and social policy
advisory, particularly in the education field. Currently, she is a social
affairs officer, from the Social Development Division in UN-ECLAC,
where she actively participates in the project Alliance for the
Information Society (@LIS2) financed by the European Union,
focusing on the research area of ICT and education.
P. Vigneswara Ilavarasan(PhD-IIT Kanpur) is Associate Professor at the
Department of Management Studies, Indian Institute of Technology,
Delhi. He teaches and researches social aspects of production and
consumption of information and communication technologies in India.
Research areas include labor process in software work, small software
firms and inter-firm linkages, labor segmentation in the ICT workforce,
research and development centers of ICT multinationals in India, use of
ICTs by urban micro-entrepreneurs, ICT clusters and electronic
governance. His works have appeared in the leading international and
national journals. He is the recipient of the Prof. M. N. Srinivas
Memorial Prize, 2009 of the Indian Sociological Society and the Abdul
Al Sagar Outstanding Young Faculty Fellowship at the Indian Institute
of Technology Delhi, New Delhi. Further details are at: http://www.
tinyurl.com/vigneswara
Veronika Kalmusis Professor of Media Studies at the Institute of
Journalism and Communication, University of Tartu. Her research
interests are socialization and inter-generational relationships in the
emerging information society, and value change in transition culture.
She leads the research project Generations and Inter-Generational
Relations in the Emerging Information Society and participates in
several national and international projects, including EU Kids Online.
She has published extensively in international journals, for instance,
Childhood, Children & Society, Cyberpsychology, Discourse & Society, East
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Author biographies xi
European Politics and Societies, Journal of Baltic Studies, Journal of Children
and Media, Journal of Computer-Mediated Communication and Young.
Marissa Kissis a research analyst at National Opinion Research Center
(NORC) at the University of Chicago. Kiss has over five years of
experience performing data collection management tasks and delivery
activities including training materials development, field interviewer
training, instrument testing, data coding and analysis, and data delivery
for various large scale, multi-level research projects. Ms. Kiss recently
completed writing her master’s thesis on social inequalities in Internet
use at George Mason University.
Tanya Kolobovis a PhD student in the Department of Sociology at the
University of Haifa (Israel). Her research interests are medical
sociology, inequalities in access to health and medical information and
the effects of information and communication technologies on changes
in patients’ and physicians’ interactions.
Benjamin Lennett, Policy Director for the Open Technology Institute at
the New America Foundation, contributes to the program’s efforts to
develop and advocate policy proposals aimed at achieving universal and
affordable broadband access through policy research, writing, and
outreach. Prior to joining New America, Mr. Lennett served as Associate
Communications and Development Manager for the Media Access
Project, where he managed outreach and fundraising efforts.
Mr. Lennett holds a Bachelor’s Degree in Political Science from the
University of Florida. He is also a graduate of American University’s
School of Public Affairs, where he received a Master’s Degree in Public
Policy, with a concentration in economic and regulatory policy.
James Loseyis a fellow with the Open Technology Institute at the New
America Foundation. He focuses on communications and digital divide
issues in the United States and Europe. Mr. Losey has published articles
and chapters with Advances in Computing, Ars Technica, CommLaw
Conspectus, IEEE Internet Computing, IEEE Spectrum, and Slate. Prior to
joining New America, Mr. Losey worked with Citizens for Responsibility
and Ethics in Washington and interned in the Office of Congressman
Donald J. Cazayoux (D-LA). Before coming to Washington, D.C.,
Mr. Losey was a sound engineer and youth mentor at Verge Concerts.
Mr. Losey graduated from the University of California, Berkeley with a
BA in interdisciplinary studies with a research focus on the relationship
between power and the media. His undergraduate thesis discussed the
dilemma created by the different definitions of truth used in political
and press fields.
Randy Lynnis a PhD candidate in the Department of Sociology and
Anthropology at George Mason University. Mr. Lynn has an MA in
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xii Author biographies
Sociology from the University of Missouri-St. Louis, and is currently a
Presidential Scholar research assistant at the George Mason University
Center for Social Science Research. His research examines the
intersections of youth, education, digital technologies, and social
networks.
Mirko Marris Head of Market and Media Research at Publicitas, a leading
sales house for print and digital media in Switzerland, and board
member of IAB-Switzerland. He earned his PhD in communications
from the University of Zurich with his dissertation on the consequences
of the digital divide. His current research is focused on convergent
media use and its implications for the media and advertising industry as
well as for the methodology of audience research.
Sascha Meinrathis Vice President of the New America Foundation and
Director of the Open Technology Institute. In 2012 he was named one
of the top 100 in Newsweek’s Digital Power Index and he has been
described as a “community Internet pioneer” and an “entrepreneurial
visionary.” He is a well-known expert on community wireless networks,
municipal broadband, and telecommunications policy. In 2009 he was
named one of Ars Technica’s Tech Policy “people to watch” and is also
the 2009 recipient of the Public Knowledge IP3 Award for excellence in
public interest advocacy. Sascha founded the Commotion Wireless
Project (a.k.a., the “Internet-in-a-suitcase”) and, along with Vint Cerf, is
the co-founder of Measurement Lab (M-Lab), a distributed server
platform for researchers around the world to deploy Internet
measurement tools, advance network research, and empower the public
with useful information about their broadband connections. He
coordinates the Open Source Wireless Coalition, a global partnership
of wireless integrators, researchers, implementers and companies
dedicated to the development of open source, interoperable, low-cost
wireless technologies. Sascha has worked with Free Press, the
Cooperative Association for Internet Data Analysis (CAIDA), the Acorn
Active Media Foundation, the Ethos Group, and the CUWiN
Foundation. He blogs regularly at www.saschameinrath.com
Gustavo S. Meschis a professor at the Department of Sociology, University
of Haifa (Israel). His research interests are Internet and social media
effects on society, the diffusion of information and communication
technologies and youth media use. He served as the Chair of the
Communication and Information Technologies Section of the American
Sociological Association and is currently a member of the Board of
Directors of the Israel Internet Association.
Glenn W. Muschertis Associate Professor in the Sociology, Criminology,
and Social Justice Studies Programs at Miami University. He received
his PhD in Sociology from the University of Colorado at Boulder in
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Author biographies xiii
2002, and has been in his current position since 2003. Glenn’s areas of
scholarly interest lie in the sociological study of crime and social
problems, including the mass media framing of high profile crimes,
school shootings, missing persons, and social control through
surveillance technologies. He has published various materials in the
fields of sociology, criminology, and media studies.
Pille Pruulmann-Vengerfeldt is Associate Professor at the Institute of
Journalism and Communication, University of Tartu. She also works in
the Estonian National Museum. Her research interests focus on Internet
user typologies and user-friendly online spaces as possible venues for
participation. Her practical interests are mostly focused on public
engagement and user participation in public institutions and politics.
She is the leader of the research project Developing Museum
Communication in the 21st Century Information Environment and is
participating in several national and international projects. She has
recently published in Journal of Baltic Studies, Journal of Computer-Mediated
Communication and Journal of Children and Media.
Danica Radovanovićis a digital media specialist, and internet researcher at
the Belgrade Center for Digital Humanities. She will have defended her
dissertation on social media dynamics and communication practices
within internet communities at the University of Belgrade in 2013. She
was a Chevening PhD scholar (2009/2010) at the Oxford Internet
Institute, University of Oxford. Danica worked for the United Nations
(FAO) as an information management specialist on an international
project on technology, science and education. She has published
extensively in the fields of internet studies, social media, digital divide,
and new communication practices in academic journals, and in print and
online media: Index on Censorship, Global Voices Online, Scientific
American, Australian Science. Danica blogs at: http://www.danicar.org/
and tweets @DanicaR.
Massimo Ragnedda
, teaches mass communications at Northumbria
University (UK). In the academic year 2006/2007 he was an affiliated
visitor at the Department of Sociology, University of Cambridge (UK)
and in 2011 he was Academic Visiting Scholar at the Oxford Internet
Institute (University of Oxford, UK). He has a strong interest in
developments in new media and theories of media, communication and
culture. His recent research interests include digital divide and social
media research; and focusing on the stratification in the access and use
of the Internet. In particular he is interested in the new digital exclusion
in a society of information, where having or not having access to
information and the new public sphere may create new forms of digital
inequalities. He is the author of five books and several articles in Italian,
English and Spanish.
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xiv Author biographies
Takako Sano is Senior Researcher of the Institute for Information and
Communications Policy, Ministry of Internal Affairs and
Communications. She graduated from the Graduate School of Saitama
University for Policy Sciences in 1993. She has been working at the
Ministry of Internal Affairs and Communications since 1988, including
a stint at the Institute for Posts and Telecommunication Policy Study.
Mehdi Sematiis Professor of Communication at Northern Illinois
University. His writings on international communication, cultural
politics of globalization, Muslims and the Middle East in Western
popular and political imagination, and Iranian media and culture have
appeared in various scholarly journals. His books include Media, culture,
and society in Iran: living with globalization and the Islamic state (Routledge,
2007), New frontiers in international communication theory (Rowman and
Littlefield, 2004), and Studies in terrorism: Media scholarship and enigma of
terror (Southbound, 2003). His Persian writings include The age of CNN
and Hollywood: National interests, transnational communication (Nashr-e
Nay, 2006).
Bernardo Sorj
, (www.bernardosorj.com), is Director of the Edelstein
Center for Social Research. He was Visiting Professor in several
universities in Europe, United States and Latin America and is a retired
professor of sociology from the Federal University of Rio de Janeiro. He
is Director of Plataforma Democrática (www.plataformademocratica.
org) and coordinator of the Scielo Social Sciences English Edition (http://
socialsciences.scielo.org/scielo.php/lng_es). He is the author of 27
books and more than a hundred articles published in several languages
related to the impact of new technologies, the international system,
contemporary social theory, and Latin American development. His
recent books on the information society include Brazil@digitaldivide:
Confronting inequality in the information society (UNESCO, 2003), Internet y
pobreza (UNESCO/ Ediciones Trilce, 2005), and Information societies and
digital divides: An introduction (Polimetrica, 2008).
Ilan Talmudis an associate professor at the Department of Sociology and
Anthropology, University of Haifa (Israel). His research interests
include economic sociology, network models of social structure,
Internet research, youth online, technology and social structure, and
the social organization of venture capital.
Kairi Talvesis a researcher at the Institute of Sociology and Social Policy,
University of Tartu. Currently she is working on her PhD thesis in
sociology, focusing on the influence of flexible labor practices on worklife balance, proceeding from the conflict paradigm. Her main fields of
research are related to gender studies, more specifically to labor force
involvement, work-life balance and gender stratification of societies.
She has participated in several international research projects tackling
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Author biographies xv
gender inequalities. She has published a number of research papers in
international and national academic journals and chapters in edited
volumes.
Shu-Fen Tsengis Associate Professor in the Graduate Program of Social
Informatics at Yuan Ze University, Taiwan. She earned her PhD in
Sociology from the University of Illinois, Chicago. Her research
interests include social informatics, digital divide and social media
research. Her current research focuses on the use of social media and
its implication for reputation management and social capital.
Motohiro Tsuchiyais Professor of the Graduate School of Media and
Governance and Deputy Director of the Global Security Research
Institute (G-SEC) at Keio University in Japan. Prior to joining the Keio
faculty, he was Associate Professor at the Center for Global
Communications (GLOCOM), International University of Japan. He
researched in Washington, DC, as a visiting scholar at the Center for
International Development and Conflict Management (CIDCM),
University of Maryland, and at the Cyberspace Policy Institute (CPI),
George Washington University. From March 2008 to March 2009 he was
a visiting scholar at the MIT (Massachusetts Institute of Technology)
Center for International Studies. He is interested in the impact of the
information revolution on international relations; regulations
regarding telecommunications and the Internet; and global governance
and information technologies. He is also a member of the Information
Security Policy Council of the Japanese government. He authored
Information and global governance (Tokyo: Keio University Press, 2001, in
Japanese), Net Politics (Tokyo: Iwanami Publishing, 2003, in Japanese),
Network power (Tokyo: NTT Publishing, 2007, in Japanese), Intelligence
and national security (Tokyo: Keio University Press, 2007, in Japanese),
Network hegemony (Tokyo: NTT Publishing, 2011, in Japanese), Cyber
terrorism (Tokyo: Bungei Shunju, 2012, in Japanese), and co-authored
Cybersecurity: Public sector threats and responses (Boca Raton, FL, US: CRC
Press, 2012) and 20 other books. He earned his BA in political science,
an MA in international relations, and a PhD in Media and Governance
from Keio University.
Jan A.G.M. van Dijkis Professor of Communication Science and the
Sociology of the Information Society at the University of Twente, the
Netherlands. Van Dijk has been investigating the social aspects of
information and communication technology since 1984. His key
publication is De netwerkmaatschappij (first edition 1991), in English: The
network society in three editions (1999, 2006 and 2012). Other books in
English are Digital democracy (2000), Information and communication
technology in organizations (2005) and The deepening divide: Inequality in the
information society (2005), all Sage Publications. Van Dijk is an advisor to,
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xvi Author biographies
among others, the European Commission. Personal website: http://
www.gw.utwente.nl/vandijk
Barney Warfis Professor of Geography at the University of Kansas. His
research interests are diverse, but focus largely on the geographies of
services, telecommunications, the Internet, and time-space compression
as viewed through the conceptual lenses of social theory and political
economy. He is the author of several books and more than a hundred
journal articles.
Bridgette Wesselsis Director of the Centre of Interdisciplinary Research
in Socio-Digital Worlds and is Senior Lecturer in Sociology at the
University of Sheffield. She has conducted funded research that
addresses digital technology in public services, everyday life, public
spheres, new media, and identity. She was an expert on the EU Fifth
Framework IST programme, OST/DTI and the Royal Society cybertrust
programmes and is an expert for the EU on the social web and
communication in Europe. Her current projects are: Mainstreaming
Telehealth (ESRC and TSB); Participating in Search Design: A Study of
George Thomason’s Newsbooks (AHRC); Augmenting Participation in
the Arts (DCMS and KT). Her books include Inside the digital revolution:
Policing and changing communication with the public (Ashgate, 2007);
Information and joining up services: The case of an information guide for
parents of disabled children (Policy Press, 2002); Understanding the Internet:
A socio-cultural perspective (Palgrave, 2010), and The cultural dynamics of the
innovation of new media: The case of telematics (VDM Verlag). She has
published on digital services in journals such as New Media and Society,
The Information Society, and the Journal of Computer Supported
Communication.
James Witteis a professor of sociology and Director of the George Mason
University Center for Social Science Research (CSSR). Witte is a past
chair of the Communications and Information Technology section of
the American Sociological Association (CITASA). Witte is the author of
two books, The Internet and social inequalities (Routledge, 2010) and Labor
force integration and marital choice (Westview, 1992). In 2009, Witte was
the guest editor for a special edition of Sociological methods and research
on web based survey research. Professor Witte holds a PhD in Sociology
from Harvard University. He was previously on the faculty of
Northwestern University and received postdoctoral training in
demography from the University of North Carolina at Chapel Hill.
Yu-Ching Youis a PhD candidate in sociology at National Taiwan
University. Her research interests include non-standard employment,
social inequality and mobility. Her current research is focused on
digital inequality and exclusion, and the relationship between the
Internet and social inequality.
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Author biographies xvii
Nicole Zillien(PhD) is Assistant Professor in the Department of Sociology
at the University of Trier, Germany. Her current research interests
include media sociology, society and technology, the digital divide,
social inequalities, science communication and health-related Internet
use. Her publications have appeared in numerous books and peerreviewed journals. She has currently published a book on information
justice (together with André Schüller-Zwierlein) and is writing a
textbook on knowledge gap research (forthcoming 2014).
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Preface
This book is about connecting the fascinating and rapidly-evolving body
of multidisciplinary work in Internet studies and the network society with
the comparatively long-established body of work in the sociology of
stratification. In particular, the goal of the book is to connect studies of
digital divides (that is, unequal access to and usage of the digital sphere)
with sociological traditions for understanding social stratification
(including inequalities in wealth, moral authority, social class, prestige,
cultural capital, and political influence). Certainly, numerous sociologists
have an on-going contribution to the study of digital divides (indeed,
many of them appear in this volume), and we certainly respect the work of
the seminal academic figures in the field of digital divides. However, what
such studies at times seemed to lack was a theoretical perspective which
was strongly tied to classical (and resulting) traditions in the sociology of
stratification.
The book emerged from a scholarly discussion between the editors
(sociologists who study, among other things, mass media, and social
stratification), as to the relative under-emphasis of classical theoretical
perspectives among digital divide studies. Of course, many such studies
come from scholars outside sociology, in fields such as informatics, mass
communications, and information technology; however, it is our sense that
sociologists have something uniquely important to contribute to studies of
inequality in the network society. Given the foundational role of theories
of stratification in the development of sociology from the nineteenth
century onward, we were sure that sociology should contribute a strong
voice to on-going debates about how digital divides were articulated, and
in some cases attenuated or exacerbated, worldwide.
Around the same time that we (the editors) were wondering at the
relative underrepresentation of sociologists in this debate concerning the
emergent form(s) of inequality in the digital sphere, there appeared a text
which applied the classical schools of sociology (Durkheimian, Marxist,
and Weberian) to digital inequality in the United States: James Witte and
Susan Mannon’s (2010) The Internet and social inequalities. Indeed, the Witte
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Preface xix
and Mannon volume served as an approximate point of departure for the
volume, as the reading of their volume helped to solidify our sense that the
theoretical and empirical approaches of classical sociology had much to
say in regards to inequality in the digital sphere. While Witte and Mannon
(2010) examined the relevance of this approach to studying digital divides
in the United States, another contribution of the volume was that it laid a
rough theoretical and empirical groundwork for the application of the
approach to other countries or regions of the world. This volume is the
outgrowth of our attempt to see an international and comparative
examination of digital divides in a variety of settings across the world.
Each of the contributors to this volume was asked to consider Witte and
Mannon’s (2010) book as a point of departure, and then to add their own
interpretations and perspectives to the discussion of digital divides
observed within a specific national or regional context. There were very
few stipulations placed upon the contributors, as these would not have led
to fruitful scholarly exploration and discourse. Thus, contributors were
free to select empirical data and one or more theoretical tradition within
sociology around which they would center their discussion. The only
stipulations we set were that each chapter needed a conceptual connection
to a classical tradition of stratification in sociology, and that each chapter
should be at least in some way grounded to empirical evidence. Such a
loose set of stipulations meant that contributors were free to decide their
own conceptual and empirical/analytical strategies, and allowed
contributors to be creative and free in their contributions. However, what
was gained in the setting of general parameters for contribution is that
each of the chapters in this volume honors two crucial aspects of sociology:
first, that the discipline is based on the foundational work of its early
theorists, and second, that sociology is an empirical discipline. What was
also gained was the ability to infer comparisons among the nations and
regions studied in the various chapters, as such comparisons can emerge
along both the theoretical lines and the empirical approaches employed in
the various chapters.
This volume, the outcome of our endeavor, reflects a sociological
approach in its analysis of the international connection between the
related issues of the social inequalities, and the social consequences of the
new digital discrimination in use of new communications technologies.
Our volume contributes to the literature by collecting contributions from
many different areas of the world and by publishing them in one location.
Seeing country/region studies side by side will allow readers to understand
the similarities and differences in the digital divide phenomena observed
in the three categories of national settings, viewed via a unified lens. In
connecting information about these different social and economic areas
of the world, previously poorly connected (yet intimately related) aspects
of the digital divide can become clear. Our volume integrates the
constructionist work on digital divide, policy analysis of new digital
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xx Preface
discrimination policies, and finally offers an implied forward-looking (and
perhaps proscriptive) view of how social scientists and policy analysts can
effectively understand and respond to varying forms of new digital
inequalities. With expert contributors from a variety of areas of the world
and social science disciplines, this book turns a critical eye to the current
state of the digital divide and new social inequality practices (and policies),
while exploring the lessons learned from successes and failures in
international and comparative perspectives. We anticipate that the
comparative examination of these dynamics will be helpful to clarify the
mechanisms and consequences of the digital divide in a variety of settings.
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Introduction
Massimo Ragnedda
Northumbria University
Glenn W. Muschert
Miami University
Defined as stratification in the access and use of the Internet, the so-called
digital divide is inevitably tied with the concept of social inequalities (van
Dijk, 2005), a classic sociological concept. Strangely, the discipline of
sociology has been slow to contribute to the debate on the Internet and
social inequalities. This is surprising, because sociology has a long and
fruitful tradition of studies in aspects of social inequalities, and because
sociology has contributed to the debates about stratification more than
any other discipline. Indeed, even if social stratification is a crucial part of
all human organization ever observed, it was in the writings of the “fathers
of sociology” such as Marx, Weber, and Durkheim, that the study of this
topic became more systematic, articulated using concepts that remain with
us to this day. It is inevitable therefore, from a sociological point of view, to
study the digital divide using these conceptual and analytical tools.
Despite this, the phenomenon of the digital divide (a fundamental aspect
of social inequity in the information age) has received less sociological
attention than it should (though this is changing – see, for example,
DiMaggio et al., 2001; Witte and Mannon, 2010; Stern, 2010), at least using
the traditions within sociology.
In this volume, the analysis of the digital divide is driven by the
sociological perspective(s) and is intended to understand the nature of
social inequalities and the new digital discrimination/virtual inequality
(Mossberger et al., 2003). However, the sociological dimensions of the
digital divide are also explored in comparative perspective, as the reader
encounters studies focusing on stratification in the digital sphere, as
explored in a variety of national and cultural settings. We are interested in
the social consequences of Internet use (Katz and Rice, 2002) and how
people’s online activities are influenced by socioeconomic background
(Zillien and Hargittai, 2009), but also in a comparative global context.
The digital divide is a complex and dynamic phenomenon (van Dijk
and Hacker, 2003) and in its simplistic sense, conceptualized as a form of
stratification exhibiting itself in unequal access and use of the Internet.
This concept is typically measured via access to the Internet (versus non-
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2 Massimo Ragnedda and Glenn W. Muschert
access), number of sites at which the Internet is accessed, users’ skill at
using the Internet, amount of time spent online, and the variety of
activities carried out digitally. In its many forms, the digital divide has
more commonly been conceptualized (and measured) as the differences
between those who have access to the web versus those who do not. Clearly,
academic research should go beyond just studying access (Castells, 2001;
Stanley, 2003) because such a binary classification limits digital divide
research (Hargittai, 2002). Certainly those who are completely excluded
are at one extreme end of the digital divide, however even among those
with web access, there are nuances to the digital divide, ones which add
finer gradients to the discussion. Today the biggest concern is not always
concerning access, but the divide among information “haves” and “havenots”, resulting from the ways in which people use the Internet (Dobson
and Willinsky, 2009; Eshet and Aviram, 2006; Eshet-Alkalai and Chajut,
2009; Hargittai, 2005, 2009; Jenkins et al., 2006; Livingstone and Helsper,
2010; Perez-Tornero, 2004). In other words, differences in digital
proficiencies create new inequalities (Gui and Argentin, 2011) and are the
main focus of studies of the so-called second-level digital divide (Hargittai,
2002; van Deursen and van Dijk, 2010).
One core theme in the book is to explain how online activities vary
according to crucial sociological dimensions, including gender (Bimber,
2000; DiMaggio et al., 2001; Clark and Gorski, 2002a; Cooper and Weaver,
2003; Losh, 2003; Ono and Zavodny, 2003; Cooper, 2006), age/generation
(Loges and Jung, 2001; Soker, 2005; Palfrey and Gasser, 2008; Hargittai,
2010), education (Clark and Gorski,, 2001; Attewell, 2001; Clark and
Gorski, 2002b), income and social class/caste (Bucy, 2000; Zillien and
Hargittai, 2009), country (Chen, 2004; Chinn and Fairlie, 2007),
employment, and race/ethnicity (Hoffman and Novak, 2001; Fairlie, 2003;
Fairlie, 2004); and, further, to explain the practical consequences of these
differences, in terms of social status, power or profit. Where else to find an
arsenal of academic concepts to address such dimensions of the digital
divide than in sociology? Indeed, a sociological perspective is needed and
our goal has been to tie the study of digital divides to the concepts of social
inequality and stratification as understood within classical theories of
sociology. Stratification studies proceed from a multiplicity of approaches
including perspectives of class inequality (Scott, 2000) or other forms of
material inequality (Crompton, 1998). For social scientists who study
digital divides, it is vital to reframe the crucial concepts as social
stratification. In light of social changes and emergent social movements
(Therborn, 2000), it can be informative to reframe contemporary studies
of the digital sphere within classical perspectives of social stratification, as
studied by Marx, Weber and Durkheim.
The Marxist-derived or conflict perspective focuses on the economic
aspects of social stratification, and clearly this perspective (and its
derivatives) has been most strongly represented in the field of digital divide
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Introduction 3
studies. Classically, Marx describes the ownership of property as the basis
of class divisions, and the social stratification as inevitably tied with
economic class (1976). The scholars influenced by the Marxist approach to
social stratification tend to emphasize the sphere of production in which
the ruling class (or bourgeoisie) derives its power from its ownership and
control of the forces of production. According to some authors, the Marxist
approach is still important in the digital age, particularly after the world
economic crisis (Žižek, 2010). Various scholars weigh in on the connection:
Graham talks about a digital dark age in which the knowledge economy is
seen as alienation (2001). Lauer (2008) argues about the process of
alienation in the information economy, while Rey (2012) explains how the
social media users are subject to levels of exploitation relatively consistent
with industrial capitalism, which is a new iteration of alienation. Similarly,
Fuchs in various studies has argued that online advertising is a mechanism
by which corporations largely take advantage of Web 2.0 users (Fuchs,
2009, 2010, 2011). Vincent Mosco argued that a Marxist theory of
communications should “demonstrate how communication and culture
are material practices, how labor and language are mutually constituted,
and how communication and information are dialectical instances of the
same social activity, the social construction of meaning” (2009, 44).
Furthermore a special issue of tripleC – Open Access Journal for a Global
Sustainable Information Society edited by Fuchs and Mosco (2012) on “Marx is
back: The importance of Marxist theory and research for critical
communication studies today” shows the enduring importance of a Marxist
approach for critical communication studies. This approach is crucial in
order to understand the formation of dominant groups in the
communications sector and the capital accumulation dynamics that
reproduce social inequalities. The digital divide could be seen, in this
perspective, as a way in which the social inequalities are (re)produced (not
to mention consumed) in the digital age using the new technologies of
communication.
The Weberian perspective offers the basis for integrating what have
been considered, up to now, divergent approaches to stratification studies
(Scott, 1996). Social stratification in a Weberian approach comprises three
independent factors, each one with its own hierarchy and therefore role in
constituting social ranking: economic class, social status (prestige), and
political power (party) (Weber, 1947). The main element of his model of
social structure is the power, and this is articulated differently than in
Marx’s work, as class is based on the economic order, which rather than
being the totality of social life, is one aspect of life, albeit an important
one. The interaction among the three aspects of stratification constitutes
the way in which social hierarchies come about. Each of these elements
relates to the digital divide, because access to new technologies of
communication, digital skills/literacy, and capacity to create income
throughout the new technologies all contribute to increased political
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4 Massimo Ragnedda and Glenn W. Muschert
power, social prestige, and economic influence. The digital divide,
according to this approach, creates social inequalities in a new media
society, because it influences social status by giving increased prestige to
those in positions to use new technologies of communication, mastering
new specializations/skills, and increasing the ability of digital literati to
create new opportunities to realize their goals in social, political, or
economic spheres. In a number of studies in this volume, we observe that
the Internet is a powerful tool for indicating and maintaining social status,
and such conclusions can be immediately reflective of the Weberian
tradition. For example, a clear link emerges between education (a marker
of prestige and economic influence) and the ability to transform
knowledge (via digital fluency) into social, economic, or political
influence.
Finally, the Durkheimian perspective focuses on the importance of the
division of labor as the social mechanism that reproduces particular types
of social bonds while suppressing others. Specifically Durkheim (1984)
conceived two distinct types of inequalities: external inequality (imposed
on the individual by the social circumstances of birth) and internal
inequality (inequalities based on achieved status or individual talent).
Both of those inequalities recur in different ways in the digital age.
Durkheim also wrote about the external regulation of social behaviors, via
external forces of social control, and the individual’s internal integration
of a society’s norms and values. Thus, social solidarity reflected in the
collective social consciousness was a crucial element for any society, one
that echoes the underlying moral order which undergirds social
coherence. Of course, education was a crucial aspect of the (re)production
of the moral order in any society (Durkheim, 1956, 1961), and indeed we
find in our studies that the use of information and communication
technologies (ICTs) in education is a focus in many settings around the
world. The role of digital divides in new forms of education (including
lifelong learning) cannot be underestimated, and clearly, these connect
readily with the Durkheimian tradition.
Each of the contributing authors have been invited to discuss the
phenomenon of the digital divide as related to their chosen countries (or
regions) of expertise, using one or more of these sociological perspectives
to illustrate the dimensions of social inequalities in digital spheres.
Certainly, sociologists are adept at examining inequalities as they exist in
the world at large, yet there is much to be learned about how such
inequalities exist in the digital world. For example, do the traditional
inequalities simply replicate themselves in the digital sphere, or does the
digital divide operate under its own dynamics? Similarly, it is unclear
whether the digital divide simply exacerbates traditional inequalities, or
whether it also includes counter-trends that might mitigate traditional
inequalities, even while forming new forms of stratification. Finally, it is
unclear whether inequalities in the digital world translate culturally, or
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Introduction 5
whether they manifest themselves in culturally-specific ways. Such
comparative perspectives have also been underemphasized in the scholarly
discourse about the digital divide, and this under-emphasis leads to gaps
in our understanding of the digital divide, as social inequalities may vary
widely from country to country. This volume is a first step at addressing
this gap.
Organization of the book
In The Internet and social inequalities, Witte and Mannon (2010) present a
theoretical perspective for understanding the digital divide, and the
contributors to this volume have used Witte and Mannon’s theoretical and
empirical approaches as points of departure for their own examinations of
the digital divide in their respective settings. From this unified perspective,
the book proceeds with an introductory section, a theoretical section to
provide the conceptual framework for the volume, and five region-focused
sections: the first including case studies examining the digital divide in
highly modernized countries (the EU, the USA, and Japan), the second
in rapidly emerging world powers (Brazil, Russia, India, and China), the
third Eastern European countries (Romania, Estonia, and Serbia),
the fourth examining Middle Eastern countries (Israel, Egypt, and Iran),
and the fifth focusing on less developed countries, especially areas that
have received little study thus far (Latin America, the Former Soviet
Republics of Central Asia, countries in East Asia, and Niger).
Theoretical section
The first part of this book provides a theoretical starting point for the
volume, by exploring the digital divide as academic concepts within
stratified societies. In the first chapter, entitled “The reproduction and
reconfiguration of inequality: Differentiation and class, status and power
in the dynamics of digital divides,” Bridgette Wessels integrates the study
of digital divides with the sociology of stratification from the founding
fathers of sociology, who in the nineteenth and early twentieth centuries
grappled with the revolutionary changes of industrialization. Although in
different ways, she argues that class, status and power are key factors in
people’s ability to be included in a networked society.
In the second chapter, entitled “A theory of the digital divide,” Jan van
Dijk describes the way in which four types of access to digital media are
distributed among people with different social positions and/or personal
characteristics. Here, the digital divide is analyzed in the context of the
network society in which structural inequality is potentially growing
between the information elite, a participating majority, and those who are
excluded, as these three segments of society have differential opportunities
for connecting to the network.
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6 Massimo Ragnedda and Glenn W. Muschert
Section 2: Highly developed nations and regions
The second section concentrates on digital divides in highly developed
nations and regions, specifically the EU, the US, and Japan. In the opening
chapter of Section 2, entitled “The digital divide in Europe,” Nicole Zillien
and Mirko Marr base their analysis on the countries of the European
Union (with particular focus on Germany) showing how high status users
succeed in utilizing the Internet to increase existing resources supporting
the notion that the digital divide is an important new dimension of social
inequality.
In the fourth chapter, entitled “The Internet and social inequalities in
the U.S.,” James Witte, Marissa Kiss, and Randy Lynn consider whether the
gaps in Internet use according to income and education have persisted,
increased, or decreased as widely-used Internet applications and devices
have become ubiquitous. In the concluding chapter of Section 2, “Missing
in the midst of abundance: The case of broadband adoption in Japan,”
Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano discuss empirically
and theoretically the digital divide as it exhibits itself in Japan, using high
quality data made available by the Ministry of International Affairs and
Communications. It specifically focuses on the issues concerning
broadband and mobile Internet access and user and examines what
demographic and social-economic factors suppress the adoption of
broadband technologies.
Section 3: Rapidly developing large nations – the BRIC nations
In this section, the digital divide is analyzed in the rapidly emerging large
nations, the so-called BRIC (Brazil, Russia, India and China) nations. In
particular, in the first chapter of this section, entitled “The digital divide
in Brazil: Conceptual, research and policy challenges,” Bernardo Sorj
examines how the various levels of access to products, services, and
benefits of new ICTs affect different segments of the Brazilian population.
This case exemplifies the general argument that, from a policy perspective,
the struggle for digital inclusion is a struggle against time. In the second
chapter of this section, “Digitizing Russia: The uneven pace of progress
toward ICT equality,” Inna F. Deviatko addresses major dimensions of
Internet-related inequalities in contemporary Russia, including relevant
regional, urban/rural, income, gender, education and age-related
predictive variables commonly used in order to operationalize differences
in socioeconomic positions of individuals and families and,
correspondingly, in their access to Internet. The analysis is based on
multiple data sources – from 2007–2010 Russian Federal State Statistics
Service Household Budget Survey data to Public Opinion Research
Foundation (FOM) Internet Use Survey (2002–2011) data, and other
opinion and market research data on Internet coverage.
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Introduction 7
In the eighth chapter, “The digital divide in India: Inferences from the
information and communication technology workforce,” P. Vigneswara
Ilavarasan uses indicators delineated by the International Telecommunications Union (ITU) on core ICT indicators (2010) and by the
Organization for Economic Co-operation and Development (OECD) (2011)
to measure digital inequalities. The chapter also compares this with the
status in 1991 when the national economy was opened for liberalization,
providing possible reasons for a shrinking divide in the last two decades.
Finally, in the last chapter of this section, Shu-Fen Tseng and Yu-Ching You
examine the first and second order digital divides in newly industrialized
countries (NICs) such as Hong Kong and Taiwan, and the rapidly developing
economy of China. These are compared and tested for the normalization/
stratification hypothesis of Internet penetration. In their chapter entitled
“The digital divide in China, Hong Kong and Taiwan: The barriers of first
order and second order digital divide,” the continuous expansion of ICTs is
addressed, and this analysis reveals new disparities, specifically in the second
order digital divide – inequality in ICT usage.
Section 4: Eastern Europe
In this section, the analyses of the digital divide are oriented to understand
how and if the digital divide is reinforcing or reducing the social
inequalities in the former Communist areas, with coverage of Serbia,
Romania, Hungary, Poland, Bulgaria, and Estonia. This section opens
with a chapter entitled “The Internet and digital divide in South Eastern
Europe: Connectivity does not end the digital divide, skills do” in which
Danica Radovanović explores the social inequalities not only in the context
of technological infrastructure, but examines issues such as literacies
(information, digital, media, and network), online social networks,
knowledge gaps, and collaborative/non-collaborative practices. The
fundamental concept of social stratification is examined from sociotechnological and educational perspectives.
Next, Monica Barbovschi and Bianca Balea, present a chapter built on
the data from the EU Kids Online II project. This chapter, entitled
“Closing the gap, are we there yet? Reflections on the persistence of
second-level digital divide among adolescents in Central and Eastern
Europe,” investigates the differences in digital competencies along the
lines of socio-economical dimensions in four countries in the Central and
Eastern European region: Romania, Hungary, Bulgaria and Poland. The
authors utilize a conflict perspective which emphasizes how Internet use,
understood as a package of knowledge and skills, plays an important role
in maintaining inequalities.
In the final chapter of this section, entitled “Behind the slogan of
‘e-State’: Digital stratification in Estonia,” Veronika Kalmus, Kairi Talves
and Pille Pruulmann-Vengerfeldt demonstrate the shift in the literature to
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8 Massimo Ragnedda and Glenn W. Muschert
exploring “digital inclusion” and “digital stratification,” where qualitative
parameters of inclusion/exclusion and ICT use matter. The authors use
empirical data from several nationwide quantitative studies carried out in
Estonia – a “new” EU member state whose success in information society
development is internationally recognized.
Section 5: The Middle East region
In this section the authors examine the digital divide in the Middle East
region. We have invited scholars from Egypt, Israel, and Iran with the aim
of covering these three important countries: the first chapter was written
after the revolt that culminated with the resignation of Hosni Mubarak,
the second chapter analyses the digital divide in Israel, and finally the
digital divide is examined in the demographically young (about 70 percent
of Iran’s population is under the age of 30) and large (with a population of
70 million) country of Iran.
In the first chapter of this section, entitled “Digitally divided we stand:
The contribution of digital media to the Arab Spring,” David M. Faris
presents new data which suggests access to the Internet is still dependent
on income and country across the entirety of the Arab world. This
inequality undermines the egalitarian potential of online public spheres,
while simultaneously empowering a set of actors who are best positioned to
take advantage of their privileged access. In Egypt, a group of young, techsavvy urban elites used the power of digital activism to harness longsimmering resentment against Egyptian state practices. This online
movement culminated in the resignation of Hosni Mubarak and the
movement of the country toward more democratic and pluralist rule. Faris
explains how digital inequalities both at the level of access and at the level
of substantive input structured the Egyptian digital activist movement,
empowered some Egyptians, and marginalized the voices of other
important actors like organized labor.
In the second chapter of this section, “Explaining digital inequalities in
Israel: Juxtaposing the conflict and cultural perspectives,” Gustavo Mesch,
Ilan Talmud and Tanya Kolobov analyze the rapid expansion of Internet
adoption and its use, often associated with the formation of social
networks, the accumulation of social capital, and increasing wages. Thus, a
lack of Internet access seems to reflect other social inequalities, leading to
inequality amplification. The authors investigated gaps over time in access
and use of the Internet in Israel, moving from the central assumption that
in deeply divided societies where there is a partial, but significant, overlap
between ethnicity and the occupational structure, disadvantaged
minorities lack digital access, as they are concentrated in occupations that
are not exposed to computers and the Internet.
In the final chapter of this section, Hamid Abdollahyan, Mehdi Semati
and Mohammad Ahmadi examine dimensions of digital divide in Iran
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Introduction 9
with an emphasis on secondary digital divide. This chapter, entitled “An
analysis of the second-level digital divide in Iran: A case study of University
of Tehran undergraduate students,” is structured around two major parts.
First, the authors review and analyze data about second-level digital divide
in Iran and they discuss the historical turn in digital divide studies that
has been diverted from studying technology haves and have-nots towards
studying a skilled-based divide among different groups. Then, the authors
elaborate their digital literacy survey among undergraduate students at
the University of Tehran, offering an argument as to why they believe
second-level digital divide is an issue in Iran.
Section 6: Under-studied countries and regions
For the final section of the volume, we have invited scholars to cover some
of the under-represented and under-studied areas of the world. Naturally
it is difficult to cover all parts of the world, but we have tried to offer an
international perspective giving space also to the digital divide in Latin
America, in the Former Soviet Republics in Central Asia, in East Asia, and
finally in Sub-Saharan Africa. The section opens with a chapter that
explores the process by which ICTs are integrated and used in Latin
America, with an approach that views ICTs as instruments for addressing
the development needs of the region, paying attention to the risks inherent
in the process. Daniela Trucco Horwitz, in her chapter “The digital divide
in the Latin American context,” states that this is one of the most unequal
regions of the world and the mass dissemination of ICT could be
generating new and rapidly growing forms of stratification. In Latin
America, there are different types and levels of digital divides that operate
simultaneously. The access gap, which is still substantial, is compounded
by a second gap of use and appropriation. The analysis uses empirical data
collected through international household surveys and through
international educational assessment tests.
The chapter about the digital divide in the Former Soviet Republics of
Central Asia is written by Barney Warf and is entitled “The Central Asian
digital divide.” It traces the changing geographies of internet access in the
region in light of the legacy of Soviet policies, the uneven introduction of
fiber optic cables, the rapid growth of netizens, unequal patterns of prices,
mobile technologies, the heavy bias in favor of urban areas, and
government attempts to censor internet content.
The third chapter of this section, entitled “The double digital divide
and social inequality in Asia: Comparative research on Internet cafes in
Taiwan, Singapore, Thailand, and the Philippines,” examines the digital
divide in the East Asian context. Tomohisa Hirata, using statistical data
provided by the ITU, states that there is a significant difference in the
proportion of households with the Internet in Asia. In this chapter, this
phenomenon in Asia is designated as “the double digital divide,” which
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10 Massimo Ragnedda and Glenn W. Muschert
indicates both the digital divide within each Asian country and that
across the whole of Asia. The author discusses it from the perspective of
the cultural theory in Weberian socio-economics, drawing on extensive
ethnographic fieldwork and interviews conducted at Internet cafes which
provide relatively poor people with the Internet and personal computers
in Asian countries.
In the final chapter of this section, and indeed of the volume as a whole,
Gado Alzouma fills a void in the literature caused by the fact that
African countries are most commonly studied in relation to more
developed countries, rather than as sites of study themselves. Indeed, only
a few of the studies have so far analyzed how the use of technology relates
to economic standing, prestige acquisition and power relations, the three
dimensions of inequality and social stratification identified by Weber. For
this reason in this chapter, entitled “Dimensions of the mobile divide in
Niger,” the author explores the unequal adoption, appropriation and use
of computers in the country. Alzouma shows how access to computers,
computer ownership, and Internet use are stratified across the West
African country. The paper is based on a Weberian perspective and uses
Bourdieu’s field theory, analyzing data drawn from fieldwork and semistructured interviews carried out in the capital city, Niamey. Interview data
are supplemented using various sources such as statistics from the ITU,
from the Government of Niger and from various studies and surveys
concerning access to ICTs in Niger.
Finally, in addition to these nineteen chapters, Sascha Meinrath,
James Losey, and Ben Lennett, (director and fellows with the Open
Technology Institute at the New America Foundation), contribute a
brief Afterword entitled “Internet freedom, nuanced digital divides,
and the Internet craftsman.” They start by reminding us that “the
international consensus that communications is a fundamental human
right is emerging as we begin to understand the key role that the
Internet plays in numerous spheres of social life.” However, rather than
focus on the benefits of broadband and Internet connectivity, the
authors center their discussion on two significant dilemmas that have
received less attention from policy makers and commentators. First, the
challenges faced by the unconnected and, second, that all connectivity
is not created equal. Indeed, the authors argue that “in the Internet
age, which technologies and devices you use to connect increasingly
determines your online opportunities.” These different opportunities
are at the bases of the new digital and social inequalities in the Internet
age.
Overall, the nineteen chapters in this book provide an interwoven
analysis of the digital divide in relation with the social stratification.
Although some authors move in independent directions (whether
methodologically or theoretically), there are many areas of overlap,
providing room for distinctions and/or connections across countries,
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Introduction 11
cultures, and regions. The authors highlight the processes that bring
social inequalities to knowledge societies, and they offer a way forward
toward a comprehensive approach to the digital divide around the world.
Ultimately, they remind us how the foundations laid by the founding
fathers of sociology are extremely important as starting points to
understand how the Internet is disseminated and used and that they are
still relevant, even if not exhaustive, to understanding the current critical
issue of stratification in the digital sphere.
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Introduction 13
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14 Massimo Ragnedda and Glenn W. Muschert
Witte, J.C. and Mannon, S.E. (2010). The Internet and social inequalities. New York:
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Section 1
Theories of the
digital divide
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1 The reproduction and
reconfiguration of inequality
Differentiation and class, status
and power in the dynamics of
digital divides
Bridgette Wessels
University of Sheffield
Introduction
The development and expanding use of digital technology within
economic, political, social and cultural life on a global scale is raising
concerns about the emergence of new inequalities and the reproduction of
existing inequalities (Wyatt et al., 2000). These developments are part of
rapid social change, which is ushering in an information and networked
society (Castells, 1996, 2001; Webster, 2004). Some commentators argue
that the global informational capitalism underpinning an information
and networked society is generating increasingly fragmented and unequal
societies (Robins and Webster, 1999; Fuchs, 2008). This chapter draws on
the work of the founding fathers of sociology to address inequality in a
global information society. To trace this link, the chapter introduces the
idea of a digital divide before considering the way technology is situated in
socio-cultural change and inequality. It then discusses digital divides in
global informational capitalism and the formation of new inequalities.
This is followed by the conclusion.
Digital technology, social relations, and the digital divide
For many people across the world the pervasiveness of digital technology –
whether experienced as a presence or an absence – is significant. A
distinctive aspect to digital technology is that it is both an artifact and a
communication medium, which Silverstone and Hirsch (1994) call
“double articulation.” This is important in terms of assessing inequality in
a digitally enabled network society: it is not only the networked structuring
of the technology and the ability to access and use it that are contributing
factors in inequality but it also provides access to information and the
public sphere, which is a key resource in an information society. In overall
terms the significance of the technology lies in the way in which it is
embedded within the relations of production; in information flows; and in
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18 Bridgette Wessels
the way it underpins participation. The utilization of technology within
the economic, political, and socio-cultural processes of society shape
inequality.
One can start to assess the significance of exclusion from social
networks based on digital technology when one sees that it is the use of
technology within social relations that produces inequality. One can see
that inclusion into digitally enabled networks is significant in terms of the
opportunities people have to engage in economic life and to participate in
political, social, and cultural life. The embedding of digital technology in
social, economic, democratic process and cultural forms is materializing
and is experienced unevenly and differently by people across the globe.
The differential development and use of digital technology within contexts
of global inequality is creating a dynamic that is generating new forms of
poverty and exclusion as well as reproducing existing inequalities and
social divisions.
The current inequalities and divisions within information and
networked society are often thought about in terms of a digital divide
(Norris, 2000). The idea of a digital divide is a useful starting point in
exploring the dynamics of inequality within a global information culture
(Lash, 1999). Castells (2001) argues that the digital divide goes beyond
those who have access to the Internet and those who do not have access. He
writes that differing levels of access to, and usage of, digital services “adds a
fundamental cleavage to existing sources of inequality and social exclusion
in a complex interaction” (Castells, 2001, p. 247). The dimensions of digital
divide can be understood as the dynamic of inclusion and exclusion that
articulates the levels of digital and other resources that people have
available to them within the social divisions of society. This means that
people have unequal levels of opportunity to develop digital skills, to
participate in democratic process, and enter the labor market (Garnham,
2005). The digital divide involves social, democratic and global divides
(Norris, 2000), and is multi-dimensional (Wessels, 2010).
Some of the dimensions of the digital divide are as follows. First,
ethnicity, age, gender, levels of education and socio-economic background
and status are influential in the dynamics of the digital divide (Wessels,
2010). Second, there is a technological divide amongst world regions with
different levels of infrastructure that prevent some regions linking into a
global economy. Third, as Zillien and Marr (in Chapter 3 of this volume)
point out, there is widening knowledge gap for those with low access, low
skills, and little cultural capital to use digital resources. These dimensions
configure in different ways across the globe. In the US the ethnic divide is
still significant amongst digital inequalities (Wessels, 2010; Witte, Kiss and
Lynn, Chapter 4 of this volume). The contributors of this volume show that
the digital divide in developing countries is uneven with some cities and
regions developing rapidly whilst others are disconnected. There are
specific development needs of particular countries and if access and
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The reproduction and reconfiguration of inequality 19
support is not provided inequalities will deepen, as seen for example in the
Latin American context (Horwitz, Chapter 16 of this volume). Status and
cultural factors interact with the take up of digital services, which fosters
inequalities seen for example in Sub-Saharan Africa (Alzouma, Chapter
19 of this volume) and in Japan (Akiyoshi, Chapter 5 of this volume). Faris
(Chapter 13 of this volume) outlines the dynamics of a democratic divide
in accessing an online public sphere. The dynamics of these aspects are
fostering greater inequality globally as the gap between the wealthy and
poor widens around the digital divide (Castells, 2001).
The theoretical insights of Marx, Durkheim, and Weber about
inequality are based on greater differentiation in a capitalist economy and
its resulting organization of class, power and status in society. These
themes can be traced into the current situation of a global networked
society, its reconfiguration of class and its inequalities at local, national
and global levels (Castells, 2001; Webster, 2004). Inequalities coalesce
around the way technology is embedded within social relations.
Situating technology within the dynamics of socio-cultural
change and inequality
The social shaping approaches to technology address the way in which
technology is embedded in social relations. It argues that technology is
shaped by social factors such as economic concerns and gender relations
(MacKenzie and Wajcman, 1985). The way in which technology becomes
meaningful within social relations is through the culture in which is it
produced and consumed. Pfaffenberger (1988), for instance, argues that:
Technology expresses an embedded social vision, and it engages us in
what Marx would call a form of life, including political, social and
symbolic aspects of social life. It has a legal dimension, it has a history, it
entails a set of social relationships and it has meaning (1988, p. 244).
Robins and Webster (1999) follow a similar type of analysis in which they
see digital technology as: “articulating the social relations of the societies
in which they are mobilized …. [that includes] power relations” (p. 2).
These types of conceptualizations encompass the social relations of digital
technology, which address the social, political, and cultural dynamics of
inequality and the digital divide.
Durkheim (1984), Marx (1976), and Weber (1922) raise the issue of
inequality, and ask:
•
•
Why does the pursuit of wealth seem to generate poverty on an
unprecedented scale?
Why do the principles of liberty and equality appear to go hand in
hand with monstrous new forms of oppression? (Abrams, 1982, p. 4).
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20 Bridgette Wessels
These classical sociologists address these questions in different ways.
Weber (1922) emphasizes the development of bureaucracy, which is
related to the increase in scale of organizations and to the division of
labor. He sees distinctions between people based on class, status and
power. Weber identifies rationalization as a fine calculation of means to
ends rather than the value of ends, which celebrates efficiency in a
dominant cult of technique. The combination of divisions based on class
and status combines with rationalization to create an iron cage that locks
people into specific positions and restricted life-worlds. Each of these
positions influences the power individuals have to shape their life
chances.
Marx (1976; Marx and Engels, 1968) addresses the division of labor
and alienation within the capitalist mode of production when he
identifies alienation in the labor process and in the productive activity of
the worker. Alienation expresses the fact that the organization of
productive relationships constitutes a class system resting on the
exploitative dominance of one class by another, and the division of labor
identifies occupational specialization as the source of fragmentation of
work into routine and undemanding tasks (Giddens, 1979). For Marx the
hallmark of capitalism is the emergence of a class of producers who own
nothing but their own labor-power that they are forced to sell in return
for wages paid by the owners of the means of production. The work of
Marx (and Engels) highlights the relationships of inequality in a market
economy and in political arrangements associated with capitalism
(Abrams, 1982).
Durkheim (1984) argues that structural differentiation fosters
individualism as he observes that labor is becoming more divided and
specialized. The division of labor results from the struggle of individuals
to flourish in the face of the increasing volume and density of the
population and pressures on resources (Abrams, 1982). For Durkheim
differentiation creates inequalities that are part of a larger, more complex
social system. Within this system, institutions are important in supporting
social cohesion. Thus education is important in supporting organic
solidarity and in supporting individuals to develop specialisms so that each
could integrate into the labor market. The education system is also
significant in sustaining a sense of conscience collective – a collective sense
of values and morals – that underpins social order.
Marx (1976), Weber (1922), and Durkheim (1984) identify the
emergence of inequalities through increased differentiation in market
based economies. These inequalities are about material resources, about
personal fulfillment and enchantment, and about senses of belonging to a
community or collective. These issues are traced into global capitalism in
the following section.
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The reproduction and reconfiguration of inequality 21
Situating the dynamics of digital divides in global
informational capitalism
The innovation of digital technology alongside globalization, neoliberalism, and consumerism is generating social transformation and is
ushering in what some commentators call an “information society”
(Webster, 2004) or a “networked society” (Castells, 2001). In changes to a
network and information society there is continuity in that the economy is
still based on capitalism (Robins and Webster, 1999). The use of digital
technology in economic activity is situated within global capitalism that is
based on a networked organization of production processes and patterns
of consumption (Fuchs, 2008).
This networked organization of social and economic life is facilitated by
a digital infrastructure for an e-economy and information society
(Castells, 2001). For economies to be competitive in a global market, they
need to be connected to the digital infrastructure and they require a labor
force that has the education and skills to work in an e-economy. From the
point of view of ordinary people their life chances are linked to having the
capability to work in the e-economy to ensure employment. The acquisition
of the appropriate education and skills to enable people to engage in
economic life is differentiated amongst class, cultural capital and status,
gender, ethnicity, digital literacy and opportunities across the life course
at the local, regional, and national level. Furthermore as digital technology
is embedded in political communication, individuals need access and
skills to engage in the democratic process (Wessels, 2010). Access to social
and cultural networks is highly differentiated along class, status, and
ethnic lines in terms of cultural capital, which relates to inequality in
participation (Kolko, Nakamura and Rodman, 2000). Age and gender cuts
across all of these divisions and undermines older people and women’s
ability to engage and participate (Cockburn, 1983; Hacker, 1990).
The e-economy facilitates the agile development of global value chains
of production and consumption. Global corporations are able to produce,
distribute, and market products and services efficiently and cheaply by
taking advantage of national and regional low labor costs and just-in-time
production processes. A consequence of this type of networked process is
that it dis-empowers nation states and weakens national economies
(Castells, 2001; Freeman, 2000). This interacts with the provision of
welfare, both for Western advanced economies and for developing
countries.
In various corporate settlements after the Second World War,
governments in European nation states created types of welfare systems
that could mitigate to some degree the inequalities inherent in a capitalist
economy by providing basic support for those living in poverty and those
unemployed; by providing greater equality of opportunity through
education; and providing a universal health care system free at the point
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22 Bridgette Wessels
of delivery (Steinert and Pilgram, 2007). Although these settlements
varied between nation states, nation states took some responsibility in
addressing disadvantage (Roche, 1992). However, with the development of
globalization nation states have less power and resource to draw on to fund
national welfare support. This has disempowered nation states and is
resulting in the retrenchment of state-provided welfare.
Developing countries, each locked into their specific historical
trajectory, are experiencing new senses of disempowerment. These
countries have been disempowered from colonial and imperial rule
onwards. When seeking and being granted self-determination in terms of
gaining nation state status, these countries were, and still are, locked into
dependencies with the more advanced economies and global multinational
companies (Frank, 1969). Very often, these dependencies create the
development of underdevelopment, which reinforces poverty and limits
the available resource for such countries to develop. These dynamics are
still at work and they have an added dimension in that the speed of
development and change when harnessed to digital technology is fast and
flexible, which makes it difficult for developing countries to catch up
(Castells, 2001).
The development of networked production processes on a global scale
means that multi-nationals can exploit low labor costs in developing
countries often by using their own infrastructures, which means that
these countries are locked into dependencies. Another aspect of this is
that if countries and regions are not connected to a high quality digital
infrastructure and do not have a skilled labor force, they are locked out
of the global economy and therefore slip more into poverty. Both of these
dynamics point to the way in which neo-liberal globalization and an
e-enabled economy either exploit poorer countries or disconnect them.
This when taken with the overall rural exodus to urban areas is creating
absolute poverty for many people in developing regions, with women and
children often bearing the extreme ravages of such poverty (Castells,
2001; Goddard and Richardson, 1996).
One of the defining features of global capitalism with its digital
infrastructure is that of the networked organization of social life. In terms
of production, the organizational form that underpins is the “network”
(Castells, 2001). The network is becoming pervasive across all of social life
extending beyond the process of production into the organization of
welfare, social movements and into everyday life. Change to institutional
arrangements in society based on the network interacts with change in the
lives of individuals, as seen in the development of networked individualism
(Wellman and Haythornthwaite, 2002). Networked individualism points to
the way in which individuals create their own networks of communication
and contacts – some being strong ties others being weak ties – whereby
they manage their social lives. The transition to networked individualism
is characterized as being one that moves from “groups” with “each in their
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The reproduction and reconfiguration of inequality 23
place” to “networks” involving the “mobility of people and goods.” The rise
of networks is in the context of a market capitalist economy with its
inherent inequities.
There is continuity with the key themes that Marx, Durkheim, and
Weber identified. This is seen in the way in which production networks are
structuring work in terms of a flexible highly competitive labor market,
whereby politics and cultural life is organized via flows of information
within networks shaped by status, class and power; and the differentiation
of social life is ongoing and is accelerated with heightened senses of
individualism. Alongside these trends the state and the corporate sector
are using more and more techniques of surveillance to control populations
via rationalization. These trends – as continuations – of processes from
market based industrialization into market based networked information
society create the new conditions of inequality.
The formation of new conditions of inequality
Given the networked context of inequality, an expansion of the definition
of digital divides is one that addresses the multi-dimensional aspect of
inequality in a digital age. The multi-dimensional approach includes the
dynamics of socio-economic position, geographic location, ethnicity and
language, as well as educational capacities and digital literacy. These
dynamics are further complicated at the global level, where lower Internet
penetration in developing countries (although this can be uneven within
these countries), combined with the rapid change of the Internet-based
technological paradigm, requires that the less-developed countries have to
outperform advanced economies just to stay where they are, thus fostering
and reproducing global inequalities (Castells, 2001). Under the current
social and institutional conditions of transnational-networked capitalism
there is uneven development that is putting many at risk of poverty and
social exclusion (Wessels, 2010).
The dynamics of inclusion and exclusion require consideration of the
restructuring of the capitalist economy, its networked logic underpinned
by digital technology and trends towards post-Fordist welfare. The
dynamics of transnational informational capitalism within an ethos of
neo-liberalism is interacting with social and economic life at the local,
regional, national and global level (Room, 1995). Situations of exclusion
are experienced at the local level, which link to regional and national
economic conditions and policy, whilst also relating to trends in the global
economy (Steinert and Pilgram, 2007; Young, 2000). A phenomenology of
exclusion points to different dimensions, such as political exclusion (via
citizenship), economic exclusion (through lack of means), social exclusion
(through isolation), and cultural exclusion (through deficits in education).
Steinert’s (2007) definition captures the dynamics of exclusion, arguing
that social exclusion is a:
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24 Bridgette Wessels
…dynamic and multi-dimensional process … as the continuous and
gradual exclusion from full participation in the social, including
material as well as symbolic, resources produced, supplied and
exploited in a society for making a living, organizing a life and taking
part in the development of a (hopefully better) future (p. 5).
The dynamics of exclusion are embedded in post–Fordist relations of
production and the processes of globalization (Bauman, 1998; Hutton and
Giddens, 2001). There is a lack of employment security, with actors having
to be flexible to survive in the labor market (Sennett, 2001). There is need
for labor with skills to work as symbolic analysts (Robins and Webster,
1999) and as knowledge workers with appropriate skills and education to
use digital technology to turn information into knowledge, and knowledge
into action (Castells, 2001; Dutton, 2001). There are others who are on the
“outside” of these developments, who do not have the necessary skills and
resources, including geographical mobility to compete successfully in the
market (Bauman, 1998). Very often, these dynamics produce geographical
spaces of exclusion in the form of ghettos, run-down estates, with few local
services and a general lack of opportunity (Madanipour, 1998).
When post-Fordist trends in welfare are combined with lightly regulated
market economies, this triggers remote forms of control that reinforce
social exclusion, managed, in part, through various technologies of
surveillance. Digital technology is part of these dynamics in two main
ways. First, its networking logic makes it a perfect tool for post-Fordist and
global production processes. Second, its use within bureaucracies and by
the state means it can be used to as a tool of surveillance over the populace.
Baggulay (1994) draws these aspects together to state that advanced
nations are grouped by the ways their traditional social welfare policies are
constructed and how these influence employment and social structure. He
draws on Esping Andersen’s (1992) term “regime” to illustrate that the
relation between the state and the economy is systematically woven from a
complex of legal and organizational features. The way in which situations
of exclusion emerge and are managed is, therefore, a result of the ways in
which the economy and the state interact to produce either opportunities
for participation in open societies or it may foster increasing levels of
surveillance in society.
Theories of the way power operates in society vary (Westwood, 2002)
from ideas regarding oppression (Freire, 1972), hegemony (Gramsci,
1992), and technologies of power and discipline (Foucault, 1977). However,
with regard to digital technology, there are two main dimensions of power
and exclusion. First, access to digital technology as it materializes in the
relations of production provides the economic opportunity to participate
in the labor market and economy and thus for individuals to have some
power over their life chances. Second, digital technology gives states and
commercial organizations the potential to control individuals through the
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The reproduction and reconfiguration of inequality 25
information they can electronically gather about them. Any lack of
transparency in the workings of the state and the commercial sector is a
form of power that can either be used to incorporate or exclude. In this
context individuals need access to the data held on them and the skills,
education and power to protect their rights and identity (with the state
having the responsibility to ensure freedoms are maintained through
proper legislation).
The levels of access and the quality of resources are key aspects in
enabling individuals and groups to participate in the life of society (Pelikan
et al., 2007). The question therefore involves ensuring that individuals and
groups have access to the relevant resources to enable them to participate.
When digital technology is seen as resource then it can be seen as part of a
virtuous circle, where those with access to (fast) Internet (Fox, 2005), good
education and socio-economic background are in good positions to take
advantage of economic development. Those on the other hand who lack
access to any of these resources are at a disadvantage and at risk of exclusion.
The allocation of resources is related to positions of power, with those with
the least resources having less power in determining their futures, securities,
and freedoms to participate. Given the ways in which digital technology is
becoming embedded in the relations of production, in working life, in
public policy and in everyday life, it becomes a resource for participation –
social, economic, political, and cultural. However, this does not reduce
exclusion merely to access to digital technology, rather digital-related
resources become one aspect embedded within the multi-dimensionality of
exclusion and the digital divide.
Conclusion
The key themes that Marx, Weber, and Durkheim identified about
inequality are still relevant in the contemporary, digitally enabled,
networked society. The relevance of market positions, rationalization, and
differentiation are still key in the development of capitalism in a global
informational form. In many ways these factors have become heightened
because the digital infrastructure of global capitalism is enabling faster
and more agile production processes that push for a more individualistic
and flexible approach to the labor market. The need to control
populations remotely is pushing ever more rationalization through
increased surveillance techniques and the pervasive networked
organization of social life is undermining strong social ties and senses of
community. When these trends are combined with a retrenchment of
welfare in the West and an ever-growing gap between developed and
developing counties then the risk of exclusion is high, creating greater
inequality.
Digital technology is a key resource for accessing resources and for
participating in social life. It works in two related ways: one, as a structuring
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26 Bridgette Wessels
network for generating production and participation as an infrastructure
in global capitalism; and two, as a resource for individuals that enable
them to compete to enter the labor market; to engage in politics, culture
and education and to participate in social life. It is only one resource
amongst others and it cannot be utilized without other resources such as
education, language and writing skills, and good socio-economic
conditions. The general circumstance of an individual’s life is a
prerequisite to be able to utilize the potential of digital technology.
Therefore, people’s living conditions such as housing, health, and access
to local resources such as good food, water, transport and public utilities
and hygiene are the backdrop for making full use of the Internet.
Nonetheless, given that digital services are the vehicle for production and
participation the need to be connected is real and significant: being
disconnected from digital services pushes people into exclusion and
poverty.
These risks interact with existing social divisions such as socioeconomic status, class background, gender, age, ethnicity, levels of
education, geographical location and cultural capital. These configure
in a highly individualized market based society with weak ties and
connections. The general condition of a digital divide is one of insecurity
and uncertainty for many people. Given the complexity of differentiation
in a society organized through networks, the digital divide needs to be
considered in terms of the dynamics of inclusion and exclusion in global
informational capitalism. The multi-dimensional character of exclusion
points to the way barriers to participation configure through the lack of
different sets of resources. One dimension of exclusion is people’s access
and ability to use digital technology to support life chances and to
facilitate participation in social life. Digital technology is a key resource
for people in a networked society because it provides information and
resources, and access to online public spheres. However, the use of
digital services coalesces around social divisions, and in situations with
low resources, which adds a fundamental cleavage to existing
inequalities. Social inequality and disadvantage is being reproduced and
reconfigured within the networked society, specifically as digital divides.
The insights of the founding fathers about inequality are pertinent in
assessing the dynamics of the digital divide because inequality is being
reproduced in digital networks through differentiation, rationalization,
and individualism.
References
Abrams, P. (1982). Historical sociology. Ithaca, NY, US: Cornell University Press.
Baggulay, P. (1994). Prisoners of the Beveridge Dream? The political mobilisation
of the poor against contemporary welfare regimes. In R. Burrows and
B. Loader (eds.) Towards a post-Fordist welfare state? London: Routledge.
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Bauman, Z. (1998). Globalization: The human consequences, Cambridge, UK: Polity
Press.
Castells, M. (1996). The rise of the network society, Oxford, UK: Blackwell.
Castells, M. (2001). The Internet galaxy: Reflections on the Internet, business and society.
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Cockburn, C. (1983). Brothers: Male dominance and technological change. London:
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Dutton, D. (2001). Society on the line: Information politics in the digital age. Oxford, UK:
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Durkheim, E. (1984). The division of labor in society. London, Basingstoke, UK:
Macmillan.
Esping Andersen, G. (1992). The three worlds of welfare capitalism. Cambridge, UK:
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Foucault, M. (1977). Discipline and punish: The birth of the prison. London: Allen
Lane.
Fox, S. (2005). Digital divisions: There are clear differences among those with broadband
connections, dial-up connections, and no connections at all to the Internet/ Pew
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Frank, G. (1969). Latin America: Underdevelopment or revolution: Essays on the
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Freeman, C. (2000). Social inequality, technology and economic growth. In
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Freire, P. (1972). Pedagogy of the oppressed. London: Sheed and Ward.
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Garnham, N. (2005). Political economy of the information society. London: Taylor and
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Giddens, A. (1979). Capitalism and modern social theory: An analysis of the writings of
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Goddard, J. and Richardson, R. (1996). Why geography will still matter: What jobs
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Gramsci, A. (1992). Prison notebooks. New York: Columbia University Press.
Hacker, S. (1990). Doing it the hard way: Investigations of gender and technology.
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Hutton, W. and Giddens, A. (2001). On the edge: Living with global capitalism.
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Kolko, B., Nakamura, L. and Rodman, G. (eds.) (2000). Race in cyberspace. London:
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MacKenzie, D. and Wajcman, J. (eds.) (1985). The social shaping of technology.
Maidenhead, UK: Open University Press.
Madanipour, A. (1998). Social exclusion in European cities. London: Jessica Kingsley.
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Marx, K. (1976). Capital: A critique of political economy. Harmondsworth, UK:
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Norris, P. (2000). Digital divide: Civic engagement, information poverty, and the Internet
worldwide. Cambridge, UK: Cambridge University Press.
Pelikan, C., Pilgram, A., Steinert, H. and Vobruba, G. (2007). Welfare policies as
resource management. In H. Steinert and A. Pilgram (eds.) Welfare from below:
Struggles against social exclusion in Europe: Towards a dynamic understanding of
participation. Aldershot, UK: Ashgate.
Pfaffenberger, B. (1988). Fetishized objects and humanised nature: Toward an
anthropology of technology. Man 23, pp. 236–252.
Robins, K. and Webster, F. (1999). Times of the technoculture: From the information
society to virtual life. London: Routledge.
Roche, M. (1992). Rethinking citizenship, welfare, ideology and change in modern society.
Cambridge, UK: Polity Press.
Room, G. (1995). Beyond the threshold: The measurement and analysis of social exclusion.
Bristol, UK: Policy Press.
Sennett, R. (2001). Street and office: Two sources of identity. In W. Hutton and
A. Giddens (eds.) On the Edge: Living with Global Capitalism. London: Vintage.
Silverstone, R. and Hirsch, E. (1994). Consuming technologies: Media and information
in domestic spaces. London: Routledge.
Steinert, H. and Pilgram, A. (2007). Welfare policy from below: Struggles against social
exclusion in Europe. Aldershot, UK: Ashgate.
Steinert, H. (2007). Introduction: the cultures of welfare and exclusion. In
Steinert, H. and Pilgram, A. (eds.) Welfare policy from below: Struggles against social
exclusion in Europe. Aldershot, UK: Ashgate.
Weber, M. (1922). Economy and society: An outline of interpretive sociology. New York:
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Webster, F. (ed.). (2004). The information society reader. London: Routledge.
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Malden, UK: Blackwell Publishing.
Westwood, S. (2002). Power and the social, London: Routledge.
Wessels, B. (2010). Understanding the Internet: A socio-cultural perspective, Basingstoke,
UK: Palgrave.
Wyatt, S., Henwood, F., Miller, N. and Senker, P. (eds.). (2000). Technology and in/
equality: Questioning the information society. London: Routledge.
Young, J. (2000). The exclusive society. London: Sage.
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2 A theory of the digital divide1
Jan A.G.M. van Dijk
University of Twente
A relational view of inequality
Contemporary research of the digital divide and digital skills is marked by
a descriptive nature (van Dijk, 2006a). Inequalities are described using
simple demographics of individuals who have more or less access to
computers and the Internet and a different level of digital skills. The
explanation of these differences has received far less attention. One of the
reasons for this state of affairs is the predominance of individualistic
notions of inequality. Like most social, scientific and economic
investigations, digital divide research works based on so-called
methodological individualism (Wellman and Berkowitz, 1988).
Differential access to information and computer technologies (ICTs) is
related to individuals and their characteristics: level of income and
education, employment, age, sex, and ethnicity, to mention the most
important ones. This is the usual approach in survey research, which
measures the properties and attitudes of individual respondents. Making
multivariate analyses of several individual properties and aggregating
them to produce properties of collectivities, one hopes to find background
explanations.
This kind of research might produce useful data, but it does not
automatically result in explanations, as it is not guided by theory or by
hypotheses derived from theory. They remain on a descriptive level of
reasoning. One is not able to explain, for example, what it is about age and
gender that produces the differences observed. Another disadvantage of
the individualistic approach to inequality is the social and political effect
of simply blaming inequality of access on attributes of individuals such as a
lack of motivation or the urge to spend money on things other than digital
technology and the correction of inadequate digital skills.
An alternative notion of inequality uses a relational or network approach
(Wellman and Berkowitz, 1988). Here the prime units of analysis are not
individuals but the positions of individuals and the relationships between
them. Inequality is not primarily a matter of individual attributes but of
categorical differences between groups of people. This is the point of
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30 Jan A.G.M. van Dijk
departure of the groundbreaking work Durable Inequality by the American
sociologist Charles Tilly (1999). “The central argument runs like this: Large,
significant inequalities in advantages among human beings correspond
mainly to categorical differences such as black/white, male/female, citizen/
foreigner, or Muslim/Jew rather than to individual differences in attributes,
propensities, or performances” (p. 7). The point of departure of this notion
of inequality is that neither the essences of individuals nor the essences of
particular collectives or systems (e.g., capitalism, patriarchy) but rather the
bonds, relationships, interactions, and transactions between people. “I claim
that an account of how transactions clump into social ties, social ties
concatenate into networks, and existing networks constrain solutions of
organizational problems clarifies the creation, maintenance and change of
categorical inequality” (p. 21).
On the issues of the digital divide and digital skills the most important
categorical distinctions are employers and (un)employed, management
and employees, people with high and low levels of education, males and
females, the old and the young, parents and children, whites and blacks,
citizens and migrants. At the macro level of countries, we can observe the
categorical inequality of developed and developing countries, sometimes
indicated as countries from the North and countries from the South of the
globe. In every case, the first of these pairs is the dominant category in
almost every part of the world, the white-black distinction excluded. With
two exceptions (the aged and parents), this also goes for digital access and
skills, as we will see in the remainder of this chapter.
A first instance of the insight offered by the relational view is an
explanation of the differential appropriation of technology. Access to new
technological means is a part of this. The dominant category is the first to
adopt the new technology. It uses this advantage to increase power in its
relationship with the subordinate category. I will give a preliminary
example of the type of explanation the relational view is able to produce
here. Gender differences in the appropriation of technology start very
early in life. Little boys are the first to pick up technical toys and devices,
passing the little girls, most often their sisters and small female neighbors
or friends. These girls leave the operation to the boys, perhaps at first
because the girls are less secure in handling them. Here a long process of
continual reinforcement starts in which the girls “never” learn to operate
the devices and the boys improve. This progresses into adulthood, where
males are able to appropriate the great majority of technical and
strategically important jobs and, in practice, keep females out of these
jobs, whether they are conscious of this fact or not. This kind of
explanation will unearth more of the actual mechanisms creating
inequality than will an explanation in terms of individual attributes
(females being less technical or less motivated, etc.).
A second advantage of the relational view of inequality is the capacity to
make better distinctions between types of inequality. Individualistic
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A theory of the digital divide 31
notions of inequality produce an endless number of differences that can
be observed between individuals, with no particular priority among them.
Instead, distinctions have to be made between types of difference and
attention has to be called to the structural aspects of society who refer to
the relatively permanent and systemic nature of the differentiation called
inequality. In Tilly’s definition, inequality is the unequal distribution of
resources in society as a result of the competition of categorical pairs,
which produces systems of social closure, exploitation, and control (Tilly,
1999, pp. 7–9). Although this competition and the resulting distributions
are changing continually, the categorical pairs reproduce themselves
through mechanisms of social closure, exploitation, and control. In this
way, inequality becomes a systematic or structural characteristic of
societies. Using Tilly’s terminology, it is “durable” as soon as it depends
heavily on the institutionalization of categorical pairs in social, economic
and cultural systems such as capitalism, bureaucracy and patriarchy (p. 8).
A third advantage of the relational view is that it is not necessary to give
priority to any of the pairs in advance. Their relative importance is a
matter of empirical observation, producing different results for every
society. Moreover, the pairs overlap with individuals. Take, for instance, a
relatively poor, young, single, female, Jamaican teacher living in the United
Kingdom. Her inclusion in the categories of educational workers, young
people, and inhabitants of a developed country would put her on the
“right” side of the digital divide, as we will observe in the next four
chapters. However, being a female with relatively low income, perhaps
living alone without a partner or children to share a computer or Internet
connection, and being part of an ethnic minority means that she would
most likely be on the “wrong” side of the divide. This example shows the
complexity of this type of inequality. In this chapter we will argue that
labor market position, educational position, age, and sex, or gender, are
the most important categorical inequalities determining the present
digital divide.
A final benefit of the relational view of equality is that it directs our
attention to relative inequality between people and their positions and
resources. All too often, the metaphor of the digital divide suggests a
yawning gap and the absolute exclusion of certain people. Earlier, I
claimed that the simple picture of a two-tiered information society might
better be replaced by the image of a continuum or a spectrum of positions
across the population that is stretched when inequality increases (van Dijk,
1999). The absolute exclusion of access to digital media remains
important, even in the developed countries, but the emphasis is shifting to
the relative differences between people who already have access in a
certain way or to a particular extent. These differences are relative
inequalities of skills and usage. They are becoming even more important
in the information society and the network society. In my opinion,
individualistic notions of inequality are inadequate if one is to understand
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32 Jan A.G.M. van Dijk
these relatively new kinds of inequality as they are increasingly linked to
relationships, social networks and being first in the appropriation of
information (“information is power”).
Resources and appropriation theory
In my book, The Deepening Divide (van Dijk, 2005), I have developed a
theory based upon this relational view of inequality. I call it a resources
and appropriation theory of the diffusion, acceptance and adoption of
new technologies. The following four are the core concepts of this theory:
1 a number of personal and positional categorical inequalities in
society;
2 the distribution of resources relevant to this type of inequality;
3 a number of kinds of access to ICTs;
4 a number of fields of participation in society.
Items 1 and 2 are held to be the causes, and 3 is the phenomenon to be
explained, together with 4, the potential consequence of the whole
process. Being part of a process, 4 feeds back upon 1 and 2, as more or
less participation in several fields of society will change the relationships
of categorical inequalities and the distribution of resources in society.
Finally, a fifth state of affairs determining the type of inequality to be
explained has to be added as a side factor: the special characteristics of
information and communication technology. In this way, a dynamic
model can be drawn that forms the representation of this theory, as
illustrated in Figure 2.1.
Characteristics
of ICTs
Personal and
positional
categorical
inequalities
Distribution
of resources
Access to
ICTs
Participation
in society
Figure 2.1 A causal model of resources and appropriation theory
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A theory of the digital divide 33
The core argument can be summarized in the following statements:
1 Categorical inequalities in society produce an unequal distribution of
resources.
2 An unequal distribution of resources causes unequal access to digital
technologies.
3Unequal access to digital technologies also depends on the
characteristics of these technologies.
4Unequal access to digital technologies brings about unequal
participation in society.
5 Unequal participation in society reinforces categorical inequalities
and unequal distributions of resources.
The following personal categorical inequalities can be frequently observed in
digital divide research:
•
•
•
•
•
•
age (young/old)
gender (male/female)
race/ethnicity (majority/minority)
intelligence (high/low)
personality (extravert/introvert; self-confident/not self-confident)
health (abled/disabled).
The same goes for the following positional categorical inequalities:
•
•
•
•
labor position (entrepreneurs/workers; management/employees;
employed/unemployed)
education (high/low)
household (family/single person)
nation (developed/developing).
In most empirical observations, the first of these relational categories has
more access than does the second.
The following resources frequently figure in digital divide research,
sometimes under other labels such as economic, social, and cultural
capital:
•
•
•
•
•
temporal (having time to use digital media)
material (possession and income)
mental (technical ability; motivation)
social (having a social network to assist in using digital media)
cultural (status and preference for being in the world of digital media).
The core part of the model is a number of kinds of access in succession.
Here the multi-faced concept of access is refined and conceived as the
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34 Jan A.G.M. van Dijk
total process of appropriation of a new technology. This is partly
responsible for the theory’s name of Resources and Appropriation
Theory. To appropriate a new technology one should first be motivated
to use it. When sufficient motivation is developed one should be able to
acquire physical access to a computer, the Internet or another digital
medium. Additionally, one needs the material resources to keep using
the technology that consists of peripheral equipment, software, ink,
paper, subscriptions and so on. Having physical and material access does
not automatically lead to appropriation of the technology as one first has
to develop several skills to use the medium concerned. The more these
skills are developed the more appropriate use can be made of the
technology in several applications. The concept of usage can be
measured, among others by the observation of the frequency of usage
and the number and diversity of applications. This process is depicted in
Figure 2.2, which is the framework for the relative long exposition of the
following section.
The characteristics of ICT as a technology are sideward factors in Figure
2.1. When a technology is experienced to be complex, expensive, multifaced (multimedia) and leading to problems of accessibility and usability
this will increase access problems in general. Computer devices simply are
not equal to, for example, television sets. In the first decades of the
existence of ICT the characteristics mentioned were widespread in the
supply of this technology. In the most recent decade considerable progress
has been made in making the hardware and software concerned more
accessible and usable for larger parts of the population. Understandably,
this has reduced the gaps of digital skills and usage.
USAGE
- Frequency
- Diversity
DIGITAL SKILLS
- Content creation
- Strategic
- Information/
Communication
- Formal
- Operational
PHYSICAL AND
MATERIAL ACCESS
MOTIVATION
Figure 2.2 Four successive kinds of access in the appropriation of digital
technology
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A theory of the digital divide 35
The final factor in Figure 2.1 is the stake of the digital divide. The
consequences of unequal access of all kinds are more or less participation
in several fields of society: economic (such as jobs), social (e.g. social
contacts), political (voting and other kinds of political participation),
cultural (participating in cyber-culture), spatial (being able to lead a
mobile life) and institutional (such as realizing citizenship rights).
The following section presents the main results to date of empirical
research following the four kinds of access distinguished. Most results
presented are from the Netherlands where the author of this chapter was
able to test his theory in a large number of surveys and skill performance
tests. Most likely the state of affairs in Germany will be not much different
from the Netherlands. The only two differences between the countries are
that the Netherlands has a bit higher Internet access rate than Germany
(91 percent of Internet household access as compared to 82 percent in
2010, according to Eurostat) and a larger proportion of users with a low
educational background. The popularization of the Internet has advanced
a bit more in the Netherlands than in Germany.
Research on motivation, physical access, skills and usage
Motivation
Prior to physical access comes the wish to have a computer and to be
connected to the Internet. Many of those who remain at the “wrong” side
of the digital divide have motivational problems. It appears that there are
not only “have nots,” but also “want nots” considering digital technology.
With the advent of a new technology, acceptance problems in terms of
motivation always are highest. In the 1980s and 1990s many people gave
answers in survey questions that they did not need a computer or Internet
connection. When the technology has largely diffused in society the
motivation to obtain a computer and reach Internet access increases fast.
In countries with a high diffusion of ICTs even people that are far above
age 80 are motivated to get access, if only to communicate with their
grandchildren. In the year 2011 it was observed that 95 percent of the
Dutch population was motivated to have access to the Internet (van
Deursen and van Dijk, 2011). In the age of Internet hype and afterwards
when diffusion rose fast, research for the motivation to have access has
been relatively ignored. At the turn of the century German and American
surveys (ARD/ZDF, 1999a; NTIA, 2000) showed that the main reasons for
the refusal were:
•
•
•
no need or significant usage opportunities;
no time or desire;
rejection of the medium (the Internet and computer games as
“dangerous” media);
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36 Jan A.G.M. van Dijk
•
•
lack of money;
lack of skills.
In several European and American surveys reported between 1999 and
2003 it was revealed that half of the unconnected to the Internet at that
time explicitly responded that they would refuse to get connected, for the
list of reasons just mentioned (e.g., ARD/ZDF, 1999b) and a Pew Internet
and American Life survey (Lenhart et al., 2003).
These observations lead us to one of the most confusing myths
produced by popular ideas about the digital divide: that people are either
in or out, included or excluded. The last referenced survey revealed that
the Internet population in fact is ever shifting (Lenhart et al., 2003). First,
there are so-called intermittent users: people who go offline for extended
periods for some reason. A second often unnoticed group is the drop-outs
that more or less permanently lost connection to the Internet. Their
number was 10 percent of the American population in 2002 (Lenhart et
al., 2003). The next group is the “net-evaders” that simply refuse to use the
Internet and it does not matter whether they have the resources or not
(among them older managers charging their secretaries to use e-mail and
search the Internet and persons being proud of not using that “filthy
medium” or operating computers as that is deemed to be “women’s work”
by some macho-male workers). However, the number of intermittent users,
drop-outs and net-evaders is decreasing as the technology becomes a
necessary tool for daily life. In the year 2011 the proportion of drop-outs
in the Dutch population fell to 9 percent among a total of complete nonusers also comprising 9 percent. The most important reasons for complete
non-use and for drop-out from earlier use are lack of interest (47 percent),
feeling too old to use it (26 percent), not needing it (22 percent), and
having insufficient skills to use it (15 percent) (van Deursen and van Dijk,
2011). However, the most important result of this 2011 survey was that only
7.3 percent of non-users in the Netherlands were prepared to potentially
use the Internet in the future. So, in this country the hard core of refusing
non-users has already been reached.
The ever-shifting Internet population focuses our attention on a
second, perhaps even more important myth produced by the misleading
dichotomy of the digital divide. This is the assumption that those who have
a computer or Internet connection are actually using it. Many presumed
users use the computer or the Internet only once a week or a couple of
times a month, a few people even never use them. Measuring computer
and Internet access in survey questions often conflates possession or
connection with use or usage time. Time diary studies and the like show
much larger differences or divides between categories of people as will be
argued in the subsection on usage below.
The factors explaining motivational access are both of a social or
cultural and a mental or psychological nature. A primary social
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A theory of the digital divide 37
explanation is that “the Internet does not have appeal for low-income and
low-educated people” (Katz and Rice, 2002, p. 93). To dig deeper into the
reasons for this lack of interest it seems appropriate to complete the largescale surveys with qualitative studies in local communities and cultural
groups. This was done for instance by Laura Stanley in a San Diego study
in poor Latino and African American working class neighborhoods
(Stanley, 2001) and by the University of Texas in poor communities of
Austin (Rojas et al., 2004). They discovered the importance of traditional
masculine cultures (rejecting computer work that is not “cool” and
“something girls do”) and of particular minority and working class
lifestyles.
However, most pronounced are mental and psychological explanations.
Here the phenomena of computer anxiety and technophobia come
forwards. Computer anxiety is a feeling of discomfort, stress, or fear
experienced when confronting computers (Brosnan, 1998; Chua, Chen
and Wong, 1999; Rockwell and Singleton, 2002). Technophobia is a fear of
technology in general and distrust in its beneficial effects. According to a
representative UCLA survey of 2003, more than 30 percent of new
American Internet users reported that they were moderately to highly
technophobic and the same applied to 10 percent of experienced Internet
users (UCLA, 2003, p. 25). Computer anxiety and technophobia are still
major barriers to computer and Internet access in many countries,
especially among seniors, people with a low educational level and a part of
the female population. These phenomena are decreasing, but do not
completely disappear with a further diffusion of computers and Internet
access in society.
The continuation of anxiety is partly explained by personality
characteristics. The Big Five personality dimensions (agreeableness,
conscientiousness, neuroticism, extraversion, and openness) are known to
be related to computer use, attitude and stress (Hudiburg, 1999). For
example, neuroticism aggravates problems experienced in approaching
and using computers and extraversion alleviates them. See Hudiburg
(1999) and Finn and Korukonda (2004) for the personality dimensions
related to computer use.
Physical and material access
The overwhelming majority of digital divide investigations are dedicated
to the observation of divides of physical access to personal computers and
the Internet among demographical categories that are obvious in this
respect: income, education, age, sex, and ethnicity. The first nation-wide
surveys in the developed countries at the end of the 1990s and the turn of
the century all showed growing gaps of access between people with high
and low income or education and majority ethnicities as compared to
minority ethnicities. However, the gender physical access divide has closed
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38 Jan A.G.M. van Dijk
in those years, complete closure for this gap only happened in the
Northern American and North-Western European countries. Considering
age, the relationship is curved: physical access peaks in the age group of 25
to 40 and sharply declines afterwards. Clearly, the youngest generation
and women benefit from the household possession of computers, as
households are the most familiar survey unit of measurement. From the
years 2000–2002 onwards the physical access divides in the northern
European, American and Eastern-Asian developed countries started to
decline as the categories with high income and education reached partial
saturation and people with lower income and education started to catch
up (NTIA, 2002; Horrigan and Rainie, 2002; Eurobarometer 56–63,
2001–2010). However, in the developing countries the physical access
divide kept widening and is still widening (United Nations Statistics
Division, 2004; van Dijk, 2005).
Probably, the path of the physical access divide follows the familiar
S-curve of the adoption of innovations. However, the path is much more
complex and differentiated among groups of the population than the
S-curve projects and there are serious problems with mainstream diffusion
theory considering computer and Internet technology (see van Dijk, 2005,
p. 62–65). One of these problems is treated by Norris (2001) who makes a
distinction between normalization and stratification models of diffusion.
In the normalization model it is presupposed that the differences between
groups only increase in the early stages of adoption and that differences
disappear with saturation in the last stages. In the stratification model it is
assumed that first, there is a different point of departure of the access
curve for the higher and the lower social strata and second, a different
point of arrival: for some strata it might never reach 90 to 100 percent.
The two models lead to quite different projections of the evolution of
the digital divide. (See Figure 2.2 above.) This figure compares the curve
of adoption of the highest and lowest social strata in terms of physical
access. In all countries, there is higher access for people with high
education and income and a low age and there is lower access for people
with low education and income and a high age. It shows how they come
together after reaching a particular tipping point and in this way gradually
close the physical access divide. The model projects (almost) complete
future closure when a normalization model applies and the continuation
of a (smaller) gap when the stratification model applies. In the Netherlands
and other rich countries it seems that the normalization model applies
(van Deursen and van Dijk, 2011); in poorer countries the stratification
model gives a better reflection of the current and the probable coming
situation. The developed countries on average crossed the tipping point
between the years of 2000 and 2005. The developing countries have not yet
reached this state (see the annual ITU (International Telecommunications
Union) figures of the diffusion of PCs and Internet connections across
countries with different level of development [United Nations Statistics
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A theory of the digital divide 39
Division, 2004]). A tipping point is a concept of network theory. It refers to
a sudden acceleration or slow-down in the diffusion of an innovation.
Concerning the digital divide two tipping points appear. The first is the
acceleration that happens when sufficient other people are connected to a
network; then it makes more sense to also connect. This occurs at around
20 to 25 percent of diffusion. The higher social strata and the young are
the first to experience this drive to connect. In this way the divide
broadens. The second tipping point happens when a majority is connected
and saturation sets in, usually at around a two-thirds access rate. On this
occasion the lower social strata and the seniors are starting to catch up
and the divide narrows. It is this second point that we are talking about
here and that is indicated in Figure 2.3.
The background variables mentioned reveal that material and social
types of inequality are prevalent in digital divide research explaining
differences of physical access. The concepts of economic, social, and cultural
capital are the most popular ones. Others defend a resource based approach
(van Dijk et al.. 2000; de Haan, 2003; Dutta-Bergman, 2005). The author of
this chapter combines a resource based and a network approach that focuses
on social positions (van Dijk, 2005). According to this theory, differences of
physical access are related to a distribution of resources (temporal, mental,
material, social and cultural) that in turn is explained by personal categories
such as age, sex, intelligence, personality and ability and positions in society
(of labor, education and household position).
Stratification
Normalization
Situation
Developing countries
Situation
Developed countries
Timeline
First
tipping point
Second
tipping point
Figure 2.3 Evolution of the digital divide of physical access in time (line below: access
of categories of low education, low income and higher age; line above:
access of categories of high education, high income and lower age)
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40 Jan A.G.M. van Dijk
Unfortunately digital divide research with a focus on physical access is
rather descriptive and does not relate to such theories. The most common
exception is the S-curve of adoption derived from diffusion of innovations
theory and partly reflected in Figure 2.3.
Next to physical access the broader concept of material access can be
distinguished. This applies when not only the core hardware of a
computer, smart phone or Internet connection is considered but also
peripheral equipment, materials such as paper and ink, software and not
forgetting subscriptions. They comprise a growing part of the total
expenses for digital media. While hardware costs for single devices tend to
decline, the number of devices purchased these days tends to rise.
Evidently, sufficient income remains an important condition here. So,
when the physical access gap is closing, income inequalities remain
important for material access at large.
Digital skills
After having acquired the motivation to use computers and some kind of
physical access to them, one has to learn to manage the hardware and
software. Here the problem of a lack of skills might appear, according to
the model in Figure 2.2. This problem is framed with terms such as
“computer, information or multimedia literacy” and “computer skills” or
“information capita.” Steyaert (2000) and van Dijk (1999 2003, 2005)
introduced the concept of “digital skills” as a succession of several types of
skill. The most basic are “instrumental skills” (as per Steyaert) or
“operational skills” (as per van Dijk), the capacities to work with hardware
and software. These skills have acquired much attention in the literature
and in public opinion.
The most popular view is that skills problems are solved when these
skills are mastered. However, many scholars engaged with information
processing in an information society have called attention to all kinds of
content-related skills required to successfully use computers and the
Internet. Steyaert distinguishes between “structural skills” and “strategic
skills.” Van Dijk (2005) proposed a comparable distinction between
“information skills” and “strategic skills.” Information skills are the skills
to search, select, and process information in computer and network
sources. They can be defined as the capacities to use computer and
network sources as the means for particular goals and for the general goal
of improving one’s position in society.
In the last four years the author of this chapter and his Ph.D. student
Alexander van Deursen have considerably refined the concept of digital/
Internet skills into six types of digital/Internet skills and several kinds of
measurement ranging from large-scale surveys to performance tests of
Internet tasks in a media laboratory (van Deursen and van Dijk, 2010). The
following medium-related and content-related Internet skills have been
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A theory of the digital divide 41
Medium-related
distinguished and (already) partly measured, as in Figure 2.4. The focus of
Internet skills can easily be enlarged to encompass other digital media.
Very little scientific research has been done on the actual level of
digital skills possessed by people. Unfortunately it is extremely difficult
to determine the actual level because most digital skills are not the result
of computer courses, but of learning through practice in particular
social user environments (van Dijk, 2005). So far, there are only few
estimates of skills. A number of large-scale surveys have revealed
dramatic differences of skills among populations, also among
populations of countries with large new media diffusion (van Dijk, 2005;
Warschauer, 2003). However, these surveys measure the actual level of
digital skills possessed only by questions asking respondents to estimate
their own level of digital skills. This kind of measurement has obvious
problems of validity (Hargittai, 2002; Merritt, Smith and Renzo, 2005;
Talja, 2005).
Measurements of real performances only occur in small educational
settings or as a part of computer classes. The problem of these
measurements is that they are fully normative: whether the goal of a
particular course has been reached. A problem for both types of
measurements, surveys and course exams is that they mostly use a limited
definition of digital skills that does not go beyond the operational skills
listed in Figure 2.4. There is virtually no attention to the “higher” contentrelated skills mentioned in this figure.
Operational Skills: actions required to operate a digital medium
(‘button knowledge’)
Formal Skills: handling the formal structures of the medium; here:
browsing and navigating
Content-related
Information Skills: searching, selecting and evaluating information
in digital media, e.g. search engines
Communication Skills: mailing, contacting, creating online
identities, drawing attention amd giving opinions
Strategic Skills: using the digital medium as a means to achieve
particular professional and personal goals
Content-creation Skills: making contributions to the Internet with
a particular plan or design
Figure 2.4 Six types of digital skills applied to Internet skills
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42 Jan A.G.M. van Dijk
The only way to obtain a valid and complete measurement of digital
skills is to charge people with performance tests of computer and Internet
tasks that they regularly meet in daily life. Performance tests have so far
only been done by Hargittai (2002). She charged 54 demographically
diverse American experimental subjects with five rather different Internet
search tasks that belong to the information skills (as in Figure 2.4). The
results revealed enormous differences of accomplishment of these tasks
and the time needed for them.
The labor-intensive performance tests of van Deursen and van Dijk in a
university media lab where they invited a cross-section of the Dutch
population (adding up to more than 300 people) to perform nine
comprehensive Internet tasks during 1.5 hours, have provided a more valid
picture of the actual skills possessed by people (van Deursen, 2010). So far,
operational, formal, information and strategic Internet skills have been
measured (van Deursen and van Dijk, 2010). At the time of writing the
communication and content-related skills are being tested.
The main conclusion of these tests is that in these tasks Dutch citizens
showed a fairly high-level of operational and formal skills. On average 80
percent of the operational skill assignments and 72 percent of the formal
skill assignments were successfully completed. However, the levels of
information skills and strategic Internet skills attained were much lower.
Information skill assignments were completed on average by 62 percent
and strategic skill assignments on average by only 25 percent of those
subjected to these performance tests. Unfortunately, there are no
standards of comparison since comparable performance tests in other
countries are non-existent.
The second main conclusion was that there were significant
differences of performance between people of different ages and
education. The most important factor appeared to be educational
background. People with higher education perform better on all skills
than people with a lower educational background. Age primarily appears
to be a significant contributor to medium-related skills. Younger people
perform better on these skills than older people do. However, the results
regarding content-related skills prove different. In fact, age positively
contributes to the level of content-related skills, meaning that older
people perform better in information and strategic skills than young
people on the condition that they have an adequate level of mediumrelated skills. However, due to the lack of medium-related Internet skills,
many seniors are seriously limited in their content-related skills. This
observation puts the abilities of the so-called “digital generation” in
another perspective than it is known in public opinion. It also shows that
the skills inequality problem will not automatically disappear in the
future and that substantial education of all kinds and life experience
remain vital for digital skills too. In none of the series of performance
tests done so far has any gender difference been observed, despite the
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A theory of the digital divide 43
fact that in pre-test questionnaires males indicated that their skills were
significantly better than those of females.
Usage
Evidently, the purpose of the total process of appropriation is usage,
according to Figure 2.2. Having sufficient motivation, physical access and
skills to apply digital media are necessary but not sufficient conditions of
actual use. Usage has its own grounds or determinants. As a dependent
factor it can be measured in at least four ways:
1
2
3
4
usage time and frequency;
number and diversity of usage applications;
broadband or narrowband use;
more or less active or creative use.
In the remainder of this chapter I will concentrate on the first two ways.
Current computer and Internet use statistics are notoriously unreliable
with their shifting and divergent operational definitions of use, most often
made by market research bureaus. They only give some indication how
much actual use differs from physical access. Clearly, actual use diverges
far from potential use. In the U.S. more exact measures of daily, weekly or
monthly Internet use are reported in the annual surveys of, for instance,
the Pew Internet and American Life Project (www.pewinternet.org) and
the UCLA Internet Reports (www.digitalcenter.org). In Europe the same is
done by the annual Eurobarometer and Eurostat statistics. However, the
most valid and reliable estimations of actual usage time are made in
detailed daily time diary studies that are representative for a particular
country. They sometimes produce striking results. For example the Dutch
Social and Cultural Planning Agency found in a 2001 time diary study that
the number of weekly hours of computer and Internet use of males at that
time was double as compared to females (Steyaert and de Haan, 2001). Ten
years later this gender gap of computer and Internet usage time has almost
closed in the Netherlands (van Deursen and van Dijk, 2011). Anyway, this
still means that when a physical access gap for a particular social category
closes, this does not mean that the comparable usage gap also disappears.
This goes for frequency and time of usage but also for usage applications
and the other two factors mentioned above. For example, in all countries
males and females still have different preferences for particular Internet
applications. We will see that there is still a gender usage gap in terms of
applications.
A usage factor that is likely to equalize first is usage time. In 2010, van
Deursen and van Dijk observed for the first time in history that Dutch
people with low education were using the Internet in their leisure time for
more hours a day than people with high education, specifically 3.2 hours a
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44 Jan A.G.M. van Dijk
day against 2.6 hours. This turned the computer and Internet usage time
of the social classes in terms of education completely upside down as
compared to the situation in the 1980s and 1990s when usage was
completely dominated by the high educated. This was seen as a sign of the
growing popularization of the Internet. This medium is merging
completely with daily life and everyday activities and has become an
essential facility for the large majority of people in the developed
countries.
With this observation in mind it becomes relevant to look at the number
and diversity of usage applications. What are the people with lower and
higher education doing on the Internet? It appeared that people with low
education used a smaller number of applications but for a much longer
period of time. Popular applications requiring a relative long usage time
for people with low education were chatting, online gaming, receiving
audio-visual programs, social networking and trading places for products
(e.g. eBay). Chatting and online gaming were the only Internet
applications that were used significantly more by people with low
education than with high education in the Netherlands.
These observations are confirmations of the thesis of the appearance of
a so-called usage gap in terms of computer and Internet use that was
suggested by van Dijk (1999, 2003, 2005), Bonfadelli (2002), Park (2002),
Cho et al., (2003), Zillien and Hargittai (2009) and others. The basic
statement is that some sections of the population will more frequently use
the serious applications with the highest advantageous effects on capital and
resources (work, career, study, societal participation etc.), while other
sections will use the entertainment applications with no, or very little,
advantageous effects on capital and resources. This statement was first
applied to people with low and high education, by van Dijk, Bonfadelli and
others, in this way framing an education usage gap. This thesis is clearly
related to the knowledge gap thesis of the 1970s (Tichenor et al., 1970) that
stated that the high educated derived more knowledge from the mass
media such as television and newspapers than the low educated. Only, the
usage gap is much broader and potentially more effective in terms of social
inequality than the knowledge gap because the usage gap concerns
differential uses and activities in all spheres of daily life, not just the
perception and cognition of mass media.
An education usage gap was confirmed in an Internet usage trend
survey in the Netherlands (van Dijk and van Deursen, 2012). Of the 31
Internet applications investigated (15 applications labeled “serious,” 6
labeled “entertainment,” and 10 “neutral,” being “general every-day life
applications” such as e-mail and search engine use) people with low
education used significantly more entertainment than serious applications
and for the high educated it was the opposite. However, age and gender
usage gaps were also observed and in the year 2010 they were stronger
than the education usage gap (van Deursen and van Dijk, 2013). Young
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A theory of the digital divide 45
people (ages 16–35) used significantly more social networking, uploading
and downloading of music and video files, chatting, gaming and free
surfing, but also more serious applications such as news services,
discussion groups, job hunting and educational applications than people
of medium and old age. None of the 31 Internet applications were used
significantly more by people of medium and old age. A gender usage gap
was revealed by a significant higher use of 18 of the total of 31 Internet
applications by males. Females significantly more often used the
applications of e-mail, social networking, online gaming and slightly more
often used patient websites or self-help groups.
Surveying the growing number of usage application surveys in the
world, the author of this chapter draws the conclusion that, increasingly,
all familiar social and cultural differences in society are reflected in
computer and Internet use. He expects that the age usage gap will be the
first to become smaller, with a large number of Internet applications that
previously were mainly used by young people, such as social networking,
online gaming, chatting and downloading audiovisuals, spreading to
other age groups.
Research of unequal access effects
Strangely enough, research of the social effects of all these inequalities of
access is very scarce. Apparently, researchers take the advantages of access
to computers and the Internet for granted. But actually what is the stake of
these inequalities? Do people with no, or limited access of the four kinds
distinguished experience real disadvantages? So far, an important
argument has been that people still have the old channels at their disposal
that also deliver the information and communication channels they need.
For those who have no Internet, plenty of radio and television stations and
newspapers are available. For those who have no access to e-commerce, the
number of physical shops abounds. People who need new social contacts
or a romantic encounter do not necessarily need a social-networking site
or an online dating service. They still have the choice of innumerable
physical meeting places. Those who want to make a reservation can still
pick up the phone.
To investigate the real advantages and disadvantages of having or not
having access of the four kinds portrayed above, the Internet use trend
surveys of 2010 and 2011 in the Netherlands (van Deursen and van Dijk,
2010, 2011) proposed to the respondents a number of precise statements
about the potential advantages of Internet use that actually are
measurement items of the concept of participation in Figure 2.1. These
statements and their support are in Table 2.1. This is measured via the
level of support among the respondents for ten statements which indicated
the advantages of Internet usage. Among the Dutch Internet users
surveyed, the average respondent agreed with four of the ten statements,
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46 Jan A.G.M. van Dijk
as illustrated in Table 2.1. However, there are big inequalities between
people of different ages, educational levels and kinds of occupation. (See
Figure 2.5.) In the end this is the most important figure concerning the
digital divide. Here it is shown that access to computers and the Internet
really matters. That those without access have a clear disadvantage and
that those who only have access to traditional channels of information and
communication lag behind. With the growing diffusion of these digital
media in society they will probably lag further and further behind to
finally become excluded from large parts of society. This is why more or
less participation is the legitimate final effect of unequal access in the
model of Figure 2.1.
Table 2.1 Percentage of Internet users in the Netherlands giving positive answers
to potential advantages of Internet use in 2011
Statement
Percentage
Affirming
After an online application concerning a vacancy I have obtained a
job
19
Via the Internet I was able to buy a product cheaper than in a shop
80
Via the Internet I was able to sell or exchange something I otherwise
would have taken as a loss
63
Via the Internet I have discovered which political party I would like
to vote for
37
Via the Internet I have come across an association I became a
member of (such as a sports club, a cultural association, a trade
union or a political organization)
22
Via the Internet I have acquired one or more friends that I have
really met later
32
Via a dating site I have made an appointment with a potential
partner
14
Via the Internet I have discovered which medical illness I had
27
Via the Internet I have booked an economical holiday trip
60
Via the Internet I have achieved a discount on a product
42
Source: van Deursen and van Dijk, 2011.
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A theory of the digital divide 47
0
1
2
3
4
5
Total
4.0
Males
Females
4.0
3.9
16 -35
36-54
55+
2.8
7
8
9
10
5.1
3.5
Low educated
Medium educated
High educated
Lower occupations
Medium- level occupations
Higher occupations
Managers
Direction/Higher management
4.2
6
4.2
4.3
2.3
3.6
4.4
4.9
4.8
Figure 2.5 Average number of positive answers to 10 potential advantages of
Internet use in the Netherlands in 2011. Source: van Deursen & van
Dijk, 2011
Conclusion: Inequality in the network society
In the former section, we saw that unequal access to computers and the
Internet has shifted from unequal motivation and physical access to
inequalities of skills and usage. This observation is known in the literature
as the so-called Second Level Divide (Hargittai, 2002; DiMaggio et al., 2004)
or the Deepening Divide (van Dijk, 2005). With the gradual close of the
physical access divide, the digital divide problem as a whole is not solved.
On the contrary, the problem gets deeper. Differences of skills and
preferences for particular Internet use applications will become ever more
important for society. The unequal benefits of Internet use as portrayed in
Table 2.1 and Figure 2.5 are most likely caused by differences of skills,
motivations and preferences of use that belong to a particular age, gender,
educational level and occupation. Here it has to be admitted that seniors
are at a disadvantage concerning some applications in Table 2.1 as they
most likely search fewer jobs and partners online than younger people.
However, this does not apply to other applications. The same survey
revealed, for example, that young people also obtain much more
information about their medical illness via the Internet than elderly
people, who clearly need this information more (van Deursen and van
Dijk, 2011).
According to a relational view of inequality differences of physical
access (connectivity), skills and usage will become much more strategically
important in a network society. A network society can be defined as a
society that is increasingly based upon a combined infrastructure of social
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48 Jan A.G.M. van Dijk
and media networks (van Dijk, 1999, 2006b, 2012). In this society,
occupying particular positions and having relations with this position
become decisive for one’s place, opportunities and chances in society (van
Dijk, 2005). Access to and being able to use social and media networks
increasingly merge in a network society. Those who have less connection in
social networks usually also have less access to and ability to use media
networks such as the Internet. Inclusion and exclusion in both social and
media networks combined might be a powerful creator of structural
inequality in the network society. It could create the following tripartite
structure.
The core of this concentric picture of a network society portrays an
information elite of about 15 percent of the population in high-access
developed societies that has very dense and overlapping social and media
networks. They are people with high levels of income and education, they
have the best jobs and societal positions and they have more than 95
percent Internet access. These elite are accustomed to living in dense
social networks. They are extended with a large number of long-distance
ties that are part of a very mobile lifestyle.
The majority of the population (50 to 60 percent) in these societies has
fewer social and media network ties and less Internet access, skill and use.
The Internet applications used are of a relatively less serious and more of
an entertainment kind as in the case of the usage gap thesis discussed
earlier.
The Information Elite
The Participating
Majority
The Unconnected and
Excluded
Media Network Link
Social Network Link
Figure 2.6 Potential tripartite structure of the network society. Source: van Dijk
(1999, 2006, 2012)
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A theory of the digital divide 49
Finally we have the unconnected and excluded part of society that is
relatively isolated in terms of both social networks and media network
connections. They comprise at least a quarter of the population of (even)
developed societies. They consist of the lowest social classes, the
unemployed, particular elderly people, ethnic minorities and a large
group of migrants. They participate considerably less in several fields of
society.
Such a dark picture of structural inequality does not have to appear.
The inequalities of the digital divide and digital skills can be mitigated by
deliberate policies for the labor market, for the training of employees and
for educational improvements at all levels, including adult education (see
van Dijk, 2005, for a complete policy program).
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Horrigan, J. and Rainie, L. (2002). Getting serious online: As Americans gain
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A theory of the digital divide 51
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Note
1 This is an adapted version of a chapter that appeared as “Digitale Spaltung und
digitale Kompetenzen” in the German book “Informationsgerechtigkeit” (A. SchüllerrZwierlein and N. Zillien (Eds.), 2012). Berlin, Germany: De Gruyter.
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Section 2
Highly developed nations
and regions
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3 The digital divide in Europe
Nicole Zillien
University of Trier
Mirko Marr
Publicitas AG
Social inequality and the Internet
Sociologist Theodor Geiger’s work on social inequalities argues that social
strata and individual action and perception correlate, outlined as the
concept of mentality. Mentality is a psychic predisposition, an immediate
imprint on a person by their social world and the experiences made in and
radiating from it (Geiger, 1932/1972, p. 77). That is, social position and
mentality do not necessarily refer to each other, but there are status-typical
mentalities. Accordingly, there is a cover ratio between external structures
and individual psyche, which suggests that similar objective characteristics
promote the development of similar subjective characteristics. Thus,
Geiger thinks in categorical defined inequalities, without leaving aside
questions of lifestyle and inner conditions. The French sociologist Pierre
Bourdieu (1979/1982) follows a similar principle, when he defines classspecific cultural forms and from this develops his concept of habitus.
Using correspondence analysis, Bourdieu verified the existence of classspecific patterns of taste by clustering preferences in music, cooking, art,
literature, and so on. As the habitus incorporates both the impact of
external conditions and individual practices, the concept represents a link
between social structure and individual way of life. Geiger’s concept of
mentality as well as Bourdieu’s concept of habitus can be useful to explain
different practices in everyday life. Drawing on these concepts, this
chapter suggests that people’s incorporation of digital media into their
everyday lives does not happen independent of the constraints and
advantages of their existing surroundings; rather, the Internet is just one
component of people’s lives in which numerous social factors interact with
each other.
For differences in media use to be considered as a type of social
inequality, it has to be the case that the different types of media use entail
social advantages or disadvantages. From its beginning in the mid-1990s,
the idea that differences in access and usage of the Internet would result in
social inequalities accompanied the upcoming spread of the Internet.
Those disparities became socio-politically charged by their interpretation
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56 Nicole Zillien and Mirko Marr
against the background of the high priority given to the promotion of
digital technologies by European politics in the beginning of the second
millennium. This priority was driven by the belief “that the benefits of
these technologies and access to the world of information that is contained
within them is a benefit that no citizens in the twenty-first century should
be without, certainly not at least in the developed world” (Cullen, 2001,
p. 311). Reports from the European Union called this vision into question
by showing that the diffusion of digital technologies was anything but a
sure-fire success: Internet diffusion encountered limitations with just
those social groups, that were considered as “information have-nots” in
the analog world, whereas already privileged groups made the leap into
the digital age with seemingly much less effort. In the long run, the
resulting access gaps were interpreted as harbingers of a new two-class
society in the dawning age of information. This social-threat scenario had
a considerable influence on the debate (Marr, 2005) – the idea of the
digital divide caused a change in thinking on the priorities of the
promotion of digital technologies, which in the early 1990s were mainly
operated under the premise of economic development and IT-oriented
policy. The rethinking found its most visible expression in a downright
competition for initiatives – in Germany for example under the catchy
slogan “Internet für alle” (“Internet for everybody”) – and the patronage
of major political representatives, targeting the elimination of existing
barriers and securing a population-wide network. In the years that
followed, these political measures against the digital divide were
confronted with three points of criticism (Marr and Zillien, 2010):
1 Necessity: The first point of criticism expounds the problems of the
initiated measures under the aspect of necessity. Especially at the end
of the 1990s, it was asked if the current disparities in Internet access
might only be a snapshot of the diffusion process at a given moment in
time. Critics argued that though the Internet diffusion will proceed at
different speeds within different social strata, sooner or later it will
amount to a near saturation in all segments, so there was no necessity
for targeted promotion.
2Appropriateness: A second point of criticism questions whether
Internet access for all is sufficient to prevent digital divides. Critics
argue that processes of social disadvantage cannot be eliminated, but
rather might be enhanced by reaching the objective. That is because
status-specific forms of Internet usage make a significant difference
when it comes to the potentials of new technologies.
3 Relevance: Finally, the third criticism is directed at the implicit
equation of Internet access and social privileging. Critics suggest that
it is not proven that access disparities or usage differences are weighty
in terms of the distribution of social resources. It is asked to what
extent there is a capital-enhancing effect of the Internet.
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The digital divide in Europe 57
Points of criticism on efforts made
to bridge the digital divide
Necessity
Appropriateness
Relevance
Research on
internet access
Research on
internet use
Internet effects
research
Fields of digital divide research
Figure 3.1 Digital divide – points of criticism and research questions
These points of criticism correspond with three fields of digital divide
research:
1 Research on Internet access: Digital divide research in the early 1990s
drew attention to technology diffusion and focused on the causes,
extent and development of social cleavages in terms of access to
Internet technology.
2 Research on Internet usage: Later research on the digital divide
focused on the different forms of Internet usage regarding technology
use, skills and content.
3 Internet effects research: Recent research on the digital divide usually
draws on the findings of the access and usage research, without
foregrounding technology-related disparities, but rather their
influence on the distribution of capital-enhancing resources.
In the following the three sketched lines of research to investigate the
digital divide are elaborated and, with regard to the European Union,
explained in more detail.
Internet access, usage and effects
Research on Internet access
The main focus of research on Internet access is on the diffusion of the
Internet in different social groups. There is no lack of representative
longitudinal data concerning the observation of the Internet´s spread in
Europe, especially in the European Union. Corresponding studies have
been and are undertaken in many countries. However, problems are
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58 Nicole Zillien and Mirko Marr
caused by the fact that the central construct of Internet access is
operationalized very differently. Following diffusion research (Rogers,
2003), the individual adoption of a technological innovation is considered
to be completed only when five different stages of adoption have been
successfully passed through: An innovation must not only be known,
accepted and tried, but its use has to be habitualized and also integrated
into everyday life. If this criterion of diffusion research is transferred to
the spread of the Internet, access had to be linked to a regular usage over a
long period of time. Research on Internet access is rarely meeting this
requirement. Considering this, it can be said that a complete penetration
of the population by the Internet is still far away. Even if one applies the
rather soft criterion of at least using the Internet at home two or three
times a month, at present only 60 percent of the adult population in the
European Union can be classified as Internet users (see Table 3.1).
Decisive for the question of the digital divide, in terms of access research is
the fact that these access rates across different social groups and different
countries still vary considerably. An analysis of recent Eurobarometer data
shows that four European countries stand out with the highest rates of
Internet access at home: the Netherlands (94 percent), Sweden (90
percent), Denmark (88 percent), and Finland (78 percent). Generally,
there are higher rates of Internet use in northern and western countries of
the European Union. Fewer than half of the population has Internet
access at home in Hungary (48 percent), Bulgaria (43 percent), Cyprus (43
percent), Romania (39 percent), Greece (38 percent) and Portugal (35
percent) (Special Eurobarometer 362, 2011, p. 48).
The binary concepts of users and non-users of the Internet, is frequently
criticized as being of limited analytical utility. This simple concept assumes
that either all users use the Internet in the same way or that usage
differences are irrelevant. Selwyn (2004, p. 345) thus came to the
conclusion that a binary understanding of the digital divide is “limited
and rudimentary.” Jung, Qui and Kim (2001, p. 509) accused the concept
of technological determinism and Webster (2002, p. 97) noted: “[T]he
model lacks sufficient sociological sophistication.” Taking this criticism
into account, subsequent studies about digital divide tried to cover
inequalities of Internet usage in a more differentiated way.
Research on Internet usage
All in all, research on Internet usage analyzes the differences between
Internet users in three fields: 1) differences in terms of technology usage,
such as the applied Internet equipment, or the frequency of Internet use;
2) differences in skills, for example, the skills to operate a computer or the
ability to research specific information through a search engine; 3) differences in terms of used Internet content, such as information or
entertainment content.
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The digital divide in Europe 59
Differences in terms of technology usage
The Eurobarometer surveys on the information society technologies and
services – which started in 1995 and to date have been repeated more than
forty times – for example, ask for the places of Internet access (at home, at
work, at school, at university, in a friend’s house, at a public Internet access
point, on the move from a laptop, on the move from a mobile phone, and so
on) and for the frequencies of Internet use. Table 3.1 shows that in the
European Union 44 percent of the population use the Internet at home
(almost) everyday. There are considerable status-related differences: While
57 percent of high-status persons use the Internet (almost) everyday, only
one third of low-status persons do so. Besides this there are also remarkable
differences in using the Internet daily depending on age and education.
Also, the gender gap still exists to date, since 49 percent of men but only 40
percent of women use the Internet on a daily base at home (see Table 3.1).
Table 3.1 Internet use at home in the European Union (as a percentage)
Everyday/
Almost
everyday
EU27
Two or
three
times a
week
About
Two or
once in a three
week
times a
month
Less often Never
No Internet
access
44
11
4
1
2
25
13
Male
49
11
4
1
2
22
11
Female
40
11
4
1
2
28
14
15–24
74
10
2
–
1
8
5
25–39
60
13
4
2
2
12
7
40–54
42
15
6
2
3
23
9
55+
21
7
4
1
2
43
22
Sex
Age
Education (end of)
15–
13
6
3
1
1
50
26
16–19
39
14
5
2
3
25
12
20+
65
13
4
1
2
10
5
Still
studying
85
6
2
–
1
3
3
Self-positioning on the social staircase
Low
32
8
3
1
2
27
12
Medium
44
12
5
1
2
25
11
High
57
12
5
1
2
16
7
Source: Special Eurobarometer 359: 79, Europeans aged 15 and over (N= 26,574),
November–December 2010
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60 Nicole Zillien and Mirko Marr
Another differentiated examination of varieties in technology use is,
for example, made by Davison and Cotten (2003), who analyze the use of
the Internet, depending on the type of Internet connection. They note
that users with broadband connections, compared to those who are
connected to the Internet through a dial-up connection, display different
usage habits. Thus, from the type of Internet connection further layers
of the digital divide can be derived. In the European Union 55 percent
of all households have broadband access, and persons living in
households of three or more and those from large towns are more likely
to be broadband users (Special Eurobarometer 359, 2011, p. 58). The
current issue of the German (N)Onliner-Atlas (TNS Infratest, 2011), an
annual publication since 2001, shows that there is also a broadband
gender gap: 63.5 percent of men, but only 42 percent of women have a
broadband connection; furthermore, the proportion of broadband
connections, especially in the East German area, is notably below the
national average.
Such work on differences in terms of technology usage is certainly more
meaningful than the mere distinction between user and non-user, but the
focus is still on the use or non-use of Internet technology. How differently
Internet technologies are integrated into everyday life, however, depends
essentially on the Internet skills of the user, so the analysis of online skills
represents a central area of research on Internet usage.
Differences in skills
Following the Special Eurobarometer 362 (2011, p. 54) 7 percent of those
who do not have Internet access at home give as a reason that they do not
know exactly what the Internet is. This lack of knowledge is greatest in
Spain (20 percent), Belgium (19 percent) and Malta (19 percent), while
interviewees from France (3 percent), Germany (3 percent) and the
Netherlands (1 percent) almost never mention this rationale for their nonusage. In general, Eurostat data documents that the level of Internet skills
across Europe is rising. Here, Internet skills are measured using a selfassessment approach, where respondents were asked whether they 1) use a
search engine to find information; 2) send an e-mail with attached files; 3)
post messages to chat rooms, newsgroups or any online discussion forum;
4) use the Internet to make telephone calls; 5) use peer-to-peer file sharing
for exchanging movies, music and so on; 6) create a web page. Persons who
have carried out one or two of these activities are labeled as Internet users
with skills on a basic level. Those who have carried out three or four
activities relate to the group of Internet users who have skills on a medium
level and those who have carried out five or six of the six items are on a
high level. In the year 2005, 22 percent of the interviewees were classified
as users on a medium or high level, six years later, 43 percent correspond
to this group (see Table 3.2).
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The digital divide in Europe 61
Table 3.2 Level of Internet skills in the European Union (as a percentage)
2005
2006
2007
2010
2011
Never used
47
45
40
28
27
Basic level
31
30
29
32
30
Medium level
17
19
23
30
32
5
6
8
10
11
High level
Source: Eurostat data 2012, representative for persons in the EU 27 aged 16 to 74
But it is questionable if self-reports are valid measurements of actual
Internet skills. Technically speaking Internet skills can only be validly
measured by experimental tests in a controlled environment. Hargittai
(2002) emphasized early, that it was important to study differences in
Internet-related skills, as these provided the basis for the Second-Level
Digital Divide. For empirical analysis of relevant differences, test persons
were asked to search the Internet for local cultural events, particular pieces
of music or tax forms until they had found the information. The extent of
the usage competencies was here operationalized as “the ability to
efficiently and effectively find information on the Web” (Hargittai 2002: 2),
whereby the search success and the time spent for searching represented
the key criteria. In summary, it was found that the age of the respondents
was negatively correlated with their capabilities for use, while the Internet
experience and formal education had a positive effect. Correspondingly,
Alexander van Deursen shows that socio-demographic characteristics are
strongly related to Internet skills: “The most important factor –
determining all types of Internet skills – is the level of educational
attainment. The higher educated the subject, the better they perform on
operational, formal, information, and strategic Internet skills” (van
Deursen, 2010, p. 195). Another Dutch sociologist, Jan van Dijk, points to
the strategic importance of digital skills, which should be defined as
“capacities to use computer and network sources as the means for particular
goals and for the general goal of improving one’s position in society” (van
Dijk, 2005, p. 88).
Differences in terms of used Internet content
Research on Internet usage focuses primarily on different types of Internet
usage in a descriptive form without testing the individual effects of the
particular types of usage as information, communication, transaction
and entertainment. Based on Eurostat data Brandtzæg, Heim and
Karahasanovic´ (2011) build a typology of Internet users in Europe
and identify five distinct user types: Non-Users (42 percent), Sporadic
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62 Nicole Zillien and Mirko Marr
Users (18 percent), Instrumental Users (18 percent), Entertainment Users
(10 percent), and Advanced Users (12 percent). The Advanced Users show
a very broad Internet behavior and they are rather oriented towards utility
or instrumental activities than towards entertainment-related online
activities. Furthermore Zillien and Hargittai (2009) show for Germany
that an information related Internet use is positively correlated with the
socio-economic status of the users:
Overall, we find that a user’s social status is significantly related to
various types of capital-enhancing uses of the Internet, suggesting
that those already in more privileged positions are reaping the
benefits of their time spent online more than users from lower
socioeconomic backgrounds (Zillien and Hargittai, 2009, p. 287).
However, while research on Internet usage only marginally discusses or
even statistically tests short- and long-term effects of status-specific
Internet use, this is the focus of Internet effects research.
Internet effects research
Internet effects research on digital divide follows the idea that not the
differences in access and usage of the Internet itself, but the resulting
impacts should be the focus of analysis. DiMaggio and colleagues (2004)
addressed the question of whether access to the Internet leads to privileges
in the following way: “Are people who have access to the Internet any
better off – especially with respect to economic welfare (education, jobs,
earnings) or social participation (political participation, community
engagement, or receipt of government services and other public goods) –
than they would be without the Internet” (DiMaggio et al., 2004, p. 381)?
In the opinion of DiMaggio et al. the presumption that the Internet
facilitates access to education, job opportunities, better health and
political participation is a central requirement to determining whether the
digital divide should be of concern to scholars of social stratification. That
is, if we were to find no relationship between occupying a more privileged
position in society and benefitting from Internet usage then “there would
be little to debate other than percentage point difference in access and
usage over time for various groups” (Mason and Hacker, 2003, p. 41).
Selwyn (2004) states, in his theoretical work, that Internet use positively
influences productive, political, social, security-related and consumptive
participation in society. Corresponding Internet effects were examined for
example in terms of labor market integration (Boes and Preißler, 2005),
political information (see Marr, 2005, 2007), civic engagement
(Mossberger, Tolbert and McNeal, 2007) and income effects (DiMaggio
and Bonikowski, 2008). Since these activities are not about optional
aspects of life, using the Internet for certain core essential tasks can no
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The digital divide in Europe 63
longer be seen as simply a luxury good (Hargittai, 2008). Thus, it is mainly
in the domain of capital-enhancing user routines that we can speak of
digital inequality as a phenomenon of social inequality, and therefore as a
relevant object of investigation.
This is especially true for health-related Internet usage, which has the
potential to inform and empower patients. A study on European citizens’
use of E-health services (Andreassen et al., 2007) states that a total of 44
percent of the joint population of the seven countries used the Internet for
health purposes. This means, that 71 percent of the Internet users used
the medium for health-related activities, with significant differences
between the northern (74 percent), East-European (72 percent) and
southern countries (60 percent), despite the high rate in Poland (79
percent). In general, with respect to the health-related use of the online
medium, socio-structural differences become apparent: younger, higher
educated, high earning, professionals and city residents are more likely to
be users of online health information (Murray et al,. 2003, Dumitru et al.,
2007, Ybarra and Suman 2008). It is noteworthy that almost all such studies
show a significantly higher health-related Internet use by women
compared to men. At large, socio-structural differences in health-related
Internet use, however, are in line with the general patterns of digital
inequality. Those groups who use the Internet less, in general and in the
specific case of health information – the elderly, low educated, those on
low income – are simultaneously exposed to greater health risks, named by
a French study as a double divide:
We found that people who would need the Internet the most as a
potential source of health information – to compensate for a lack of
information or for remoteness from the health-care system (difficult
economic circumstances, social isolation, health problems) – are also
those who use it the least (Renahy et al., 2008, p. 9).
Those who could benefit most from a health-related Internet use belong,
therefore, to a lesser extent to the users of the respective offerings. In
another context Everett M. Rogers (1995) put forward the idea of the
“innovativeness-needs paradox.” That is, “[t]he individuals or other units
in a system who most need the benefits of a new idea (the less educated,
less wealthy, and the like) are generally the last to adopt an innovation”
(Rogers, 1995, p. 295). Since, there is evidence for positive correlation
between the Internet search for health information and the subjective
health (Wangberg et al., 2008), it is likely that a self-reinforcing effect
occurs: “[I]t seems likely that Internet use may exacerbate existing
socioeconomic status differences in health” (Wangberg et al., 2008, p. 70).
Accordingly, the Internet effects research shows that availability of the
Internet rather leads to positive effects on the part of the already
privileged. In other words: “This paradoxical relationship between
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64 Nicole Zillien and Mirko Marr
innovativeness and the need for benefits of an innovation tends to result in
a wider socioeconomic gap between the higher and lower socioeconomic
individuals in a social system” (Rogers, 1995, p. 295).
Conclusion
Regarding the development of social inequalities, differences in Internet
access and use theoretically either may lead to rising social inequalities,
to shrinking social inequalities or all in all there will be no relevant
effects of the Internet on social stratification (Hargittai and Hsieh, in
press). Even if there is anecdotal evidence for all of these models, digital
divide research empirically proves the existence of digital inequalities
which result in rising social inequalities. As we have pointed out, for
health-related Internet usage in Europe, that those with more resources
– whether technical, financial, social, or cultural – end up using the web
for more beneficial purposes. This pattern suggests that the adoption
and use of the Internet highly depends on the mentality (Geiger,
1932/1972) and respective habitus (Bourdieu, 1979/1982) of the agents.
The incorporation of new media into people`s everyday lives does not
happen independent of the constraints and advantages of existing
surroundings. Rather, the adoption and use of the Internet is just one
component of people’s lives in which numerous social factors interact
with each other. The particular uses to which status-high persons put the
Internet give them even more resources through which they can improve
their positions. At the same time, those in less privileged positions to a
lesser extent perform potentially beneficial uses of the Internet. In
consequence there will be fewer positive payoffs for people from less
privileged backgrounds, which means that the Internet will reinforce or
even increase existing social inequalities. That is to say, what knowledge
gap research forty years ago generally ascertained is true for the Internet:
“[T]he mass media seem to have a function similar to that of other social
institutions: that of reinforcing or increasing existing inequities”
(Tichenor et al., 1970, p. 170).
References
Andreassen, H. K., Bujnowska-Fedak, M. M., Chronaki, C. E., Dumitru, R. C.,
Pudule, I., Santana, S., Voss, H. and Wynn, R. (2007). European citizens’ use of
e-health services: A study of seven countries, BMC Public Health, 7, 1–7.
Boes, A. and Preißler, J. (2005). Digitale Spaltung, in SOFI, IAB, ISF and INIFES
(ed.), Berichterstattung zur sozioökonomischen Entwicklung in Deutschland – Arbeit
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Bourdieu, P. (1979/1982). Die feinen Unterschiede. Kritik der gesellschaftlichen
Urteilskraft. Frankfurt am Main, Germany: Suhrkamp.
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Brandtzæg, P., Heim, J. and Karahasanović, A. (2011). Understanding the new
digital divide. A typology of Internet users in Europe. International Journal of
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Cullen, R. (2001). Addressing the digital divide. Online Information Review, 25, 311–
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Davison, E. and Cotten, S. R. (2003). Connection discrepancies: Unmasking
further layers of the digital divide. First Monday 8 (3).
DiMaggio, P. and Bonikowski, B. (2008). Make money surfing the Web? The
impact of Internet use on the earnings of U.S. workers. American Sociological
Review, 73, 227–250.
DiMaggio, P., Hargittai, E., Celeste, C. and Shafer, S. (2004). From unequal access
to differentiated use. In K. Neckerman (ed.) Social Inequality (pp. 355–400).
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Dumitru, R. C., Bürkle, T., Potapov, S., Lausen, B., Wiese, B. and Prokosch, H.
(2007). Use and perception of Internet for health related purposes in Germany:
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Geiger, T. (1932/1972). Die soziale Schichtung des deutschen Volkes.
Soziographischer Versuch auf statistischer Grundlage. Stuttgart, Germany:
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Hargittai, E. (2002). Second-level digital divide: Differences in people’s online
skills. First Monday 7 (4).
Hargittai, E. (2008). The digital reproduction of inequality. In D. Grusky, Social
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Hargittai, E. and Hsieh, Y.P. (in press). Digital inequality. In W. H. Dutton (ed.)
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Jung, J., Qui, J. L. and Kim, Y. (2001). Internet connectedness and inequality.
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Marr, M. (2005). Internetzugang und politische Informiertheit. Zur digitalen Spaltung der
Gesellschaft. Konstanz, Germany: UVK Verlag.
Marr, M. (2007). Das Internet als politisches Informationsmedium. In K. Imhof,
R. Blum, O. Jarren and H. Bonfadelli (eds.), Demokratie in der Mediengesellschaft.
Mediensymposium Luzern Band 9 (pp. 261–284). Wiesbaden, Germany: Verlag für
Sozialwissenschaften.
Marr, M. and Zillien, N. (2010). Digitale Spaltung. In W. Schweiger and K. Beck
(eds.): Handbuch Onlinekommunikation (pp.257–282). Wiesbaden, Germany: VS
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Mason, S. M. and Hacker, K. L. (2003). Applying communication theory to digital
divide research. IT and Society, 1, 40–55.
Mossberger, K., Tolbert, C. J. and McNeal, R. S. (2007). Digital citizenship: The
Internet, society, and participation. Cambridge, Mass, US: MIT Press.
Murray, E., Lo, B., Pollack, L., Donelan, K., Catania, J., White, M., Zapert, K. and
Turner, R. (2003). The impact of health information on the Internet on health
care and the physician–patient relationship: Patient perception. Archives of
Internal Medicine, 163, 1727–1734.
Renahy, E., Parizot, I. and Chauvin, P. (2008). Health information seeking on the
Internet: a double divide? Results from a representative survey in the Paris
metropolitan area, France, 2005–2006. BMC Public Health, 8: 69.
Rogers, E. M. (1995). Diffusion of innovations, 4th edition. New York: Free Press.
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Rogers, E. M. (2003). Diffusion of innovations, 5th edition. New York: Free Press.
Selwyn, N. (2004). Reconsidering political and popular understandings of the
digital divide. New Media and Society, 6, 341–362.
Special Eurobarometer 359. (2011). “Attitudes on data protection and electronic
identity in the European Union.” Brussels: European Commission, DirectorateGeneral for Communication.
Special Eurobarometer 362. (2011). “E-communications household survey report.”
Brussels: European Commission, Directorate-General for Communication.
Tichenor, P. J., Donohue, G. A. and Olien, C. N. (1970). Mass media flow and
differential growth in knowledge. Public Opinion Quarterly, 34, 159–170.
TNS Infratest. (2011). (N)Onliner Atlas 2011. Berlin: Initiative D21.
van Deursen, A.J.A.M. (2010). Internet skills. Vital assets in an information society.
Enschede, the Netherlands: University of Twente.
van Dijk, J. (2005). The deepening divide. London: Sage.
Wangberg, S. C., Andreassen, H. K., Prokosch, H., Santana, S. M., Søren-sen, T.
and Chronaki, C. E. (2008). Relations between Internet use, socio-economic
status (SES), social support and subjective health. Health Promotion International,
23, 70–77.
Webster, F. (2002). Theories of the information society, 2nd edition. New York: Taylor
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Ybarra, M. and Suman, M. (2008). Reasons, assessments and actions taken: sex
and age differences in uses of Internet health information. Health Education
Research, 23, 512–521.
Zillien, N. and Hargittai, E. (2009). Digital distinction. Status-specific types of
Internet usage. Social Science Quarterly, 90, 274–291.
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4 The Internet and social
inequalities in the U.S.
James Witte
Marissa Kiss
Randy Lynn
George Mason University
In just over forty years the Internet has evolved from an eclectic network of
a handful of users, focused on developing a rudimentary means of
communication, to a vast worldwide web for transferring, storing and,
above all else, sharing an enormous quantity and variety of information.
The Internet and web have not only become a medium for social and
asocial use, networking and communication, but also an everyday
opportunity for cultural expression through the online activities in which
an individual engages.
However, with the development and sophistication of technology and
the Internet, opportunities to take advantage of these new technologies
are not equally distributed. As the other chapters in this volume detail,
there is a global element to Internet inequality. In this chapter, the
emphasis is on the U.S., where the digital divide remains a real and
persistent phenomenon, despite a relatively long history of Internet use
and high degree of Internet penetration.
The initial section of this chapter discusses aspects of the relationship
between the Internet and inequality from the perspective of cultural
sociology. Beginning with the work of Max Weber, the intent is to consider
why the Internet needs to be seen as more than a significant technological
development. Through its impact on individuals’ lifestyles – not simply in
what they own or the activities they participate in, but also in the
fundamental orientation as to how they conduct their lives – use of the
Internet has emerged as a critical aspect of social stratification in
contemporary U.S. life. Next, as a fundamental component of lifestyle, the
Internet’s link to the creation and maintenance of social capital is
discussed as a mechanism, whereby the Internet offers advantage to some,
while denying it to others.
The empirical section of this chapter begins with a description of the
digital divide in the U.S. through early 2011. The empirical analyses go
on to examine differences among the types of communities in which
Internet users and non-users live – in terms of the size of the community
and duration of residence, but also in the manner by which Internet
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68 James Witte, Marissa Kiss and Randy Lynn
users and non-users obtain information about their local communities.
This is followed by a discussion of the extent to which Internet users and
non-users participate in different types of groups as an organizational
context for the creation and maintenance of the social ties critical to
social capital.
Cultural perspectives on inequality
Cultural perspectives on inequality have their roots in the sociology of
Max Weber, who argued that a proper understanding of society required
due attention to the independent force of ideas. From this common
Weberian root, several distinct approaches to inequality have developed
within the cultural perspective. This section briefly describes those
common roots and discusses one particularly relevant branch, with an eye
to clarifying the relationship between the Internet and inequality from
this theoretical perspective.
To begin with, the most obvious difference between Marx and Weber’s
theories of stratification is found in Weber’s recognition of class, status
and power as analytically distinct bases of stratification within society.
Weber claimed that one can speak of a class when a group of people share
a “… specific causal component of their life chances” (Weber, 1946,
p. 181). Defined in this way, classes – as groups of similarly situated
individuals – are determined in the marketplace. Though Weber identifies
“property” and “lack of property” as the basic categories of all class
situations, he identifies two further grounds for class distinction:
“acquisition classes” and “social classes.” While property classes are
defined by the type of property owned and its potential to yield a return in
the market, acquisition classes may be traced back to the types of skills and
services individuals can offer on the market. Social classes, on the other
hand, are composed of a range of class statuses sharing a common intraand intergenerational mobility space (Weber, 1947).
Weber distinguished status stratification from class because the former
rests on a subjective sense of community, reflecting stratification
according to consumption rather than production. Moreover, the
expectation of a certain style of life on the part of group members is often
linked, according to Weber, to restrictions on social intercourse that set
status group members apart from non-members. Weber points to the
potential of status stratification to place restrictions on social intercourse
as a primary source of tension between class and status. These combine to
yield a rich and complex stratification system, which is associated with
differences in life chances and life styles. These, in turn, yield different
and exclusionary patterns of social interaction.
The work of Manuel Castells, particularly The Rise of the Network Society:
The Information Age: Economy, Society and Culture, Volume I (1996, 2000, 2010),
represents a variant of contemporary neo-Weberian sociology with
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The Internet and social inequalities in the U.S. 69
particular relevance for the topic at hand. With reference to Weber’s The
Protestant Ethic and the Spirit of Capitalism, Castells describes “the spirit of
informationalism,” which has altered but not replaced capitalism as the
dominant mode of production.
Two aspects of Castells’ work warrant emphasis here. The first is the
nature of the transformation. Castells argues that business networks,
information and communication technologies, and global competition
have combined in an historical moment to give rise to the network
society. Castells describes a unique culture: “a culture of the ephemeral,
a culture of each strategic decision, a patchwork of experiences and
interests, rather than a charter or rights and obligations as the ethical
foundation of the network society” (Castells, 2010, p. 214). Intertwined
with this culture, just as bureaucracy and rational capitalist economic
organizations were intertwined with capitalism, is the dominance of a
new standard for economic and social organization. Castells argues, for
the first time in history, the basic unit of economic and social
organization is not an individual or collective subject (e.g., a class,
corporation or state), but rather “… the unit is the network, made up of a
variety of subjects and organizations, relentlessly modified as networks
adapt to supportive environments and market structures” (Castells, 2010,
p. 214).
The second particularly relevant aspect of Castells’ treatment of the
network society is his recognition that not everyone participates equally in
the network society: “The new economy affects everywhere and everybody
but is inclusive and exclusionary at the same time, the boundaries of
inclusion varying for every society, depending on institutions, politics and
policies” (Castells, 2010, p. 161). The dynamics of inclusion and exclusion
have several implications for power and inequality in several ways. Most
obviously – and this is the focus of the empirical section of this chapter –
there are real and significant costs to being excluded from networks.
Moreover, as the advantages of inclusion are growing, the disadvantages
associated with exclusion may be growing at an even faster rate.
Furthermore, even among those included within the boundaries of a
network, the rules for participation, as well as the tangible and intangible
benefits of inclusion may not be of equal import for all members of a
network (Witte and Mannon, 2010).
Within the cultural perspective on inequality, an emphasis on
differential life chances and patterns of social interaction are common
themes that are directly relevant to the relationship between the Internet
and inequality. The Internet has become an increasingly important
medium of social interaction – both in terms of interaction between
individuals and interaction with intelligent web-based systems based on
social information and relationships.
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70 James Witte, Marissa Kiss and Randy Lynn
The Internet and social capital
Current conceptions of social capital largely derive from similar – but not
identical – articulations by three influential theorists. First, Bourdieu
defines social capital as “the sum of the resources, actual or virtual”
resulting from one’s location in and maintenance of “a durable network of
more or less institutionalized relationships of mutual acquaintance and
recognition” (Bourdieu and Wacquant, 1992, p. 14). Second, Coleman
conceptualizes social capital as an aggregate “of different entities, with two
elements in common: they all consist of some aspect of social structures,
and they facilitate certain actions of actors – whether persons or corporate
actors – within the structure.” “Productive” and “not completely fungible,”
it is unique among forms of capital in that it “inheres in the structure of
social actors and among actors” (Coleman, 1988, p. S98). Third, Putnam
(1993, p. 35) initially defines social capital as “features of social
organization, such as networks, norms, and trust that facilitate
coordination and cooperation for mutual benefit [that enhance] the
benefits of investment in physical and human capital.” In Bowling Alone,
Putnam defines social capital as “connecting among individuals... social
networks and norms of reciprocity and trustworthiness that arise from
them” (2000, p. 19).
Most broadly, then, social capital encompasses relational resources:
assets inherent in and arising from our social relationships and networks.
Because relational processes enable social capital (Portes, 1998), social
relations can be viewed as investments from which social capital is the
return (Lin, 1999; Resnick, 2002). Although some theorists – especially
Bourdieu – emphasize social capital’s prominent role in processes of
domination, most interpretations construe social capital as a positive
phenomenon, associated with such wide-ranging benefits as increased
health (Adler and Kwon, 2002), employment (Lin, 2001), and psychological
well-being (Morrow, 1999).
The relationship between Internet use and social capital has been a
topic of considerable debate. Studies arguing that Internet use negatively
impacts social capital (Kraut et al., 1998; Nie, 2001; Coget, Yamauchi and
Suman, 2002) usually rely on some variant of Putnam’s time displacement
hypothesis, in which increased Internet use is positively correlated with
decreases in other modes of communication (Williams, 2006). These
studies assert that the Internet is used largely for non-interactive purposes,
such as employment-related tasks or interactions with weaker ties,
displacing more beneficial face-to-face interactions and ties to
organizations or communities.
Displacement arguments are often linked to a broader assertion of a
recent historical or ongoing decline of social capital or the size and quality
of the social networks in which social capital is embedded (Putnam, 2000;
McPherson, Smith-Lovin and Brashears, 2006), although the methods and
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The Internet and social inequalities in the U.S. 71
conclusions of these broader studies have been subject to considerable
scrutiny and criticism (Thomson, 2005; Wang and Wellman, 2010;
Hampton, Sessions and Her, 2011).
Unlike other media linked to the decline of social capital (e.g., network
television), there are ways that the Internet may enable social interactions
and the maintenance of social ties. Moreover, Internet technologies may
enable the formation of networks and new forms of social capital not
possible in offline contexts or from the use of other media (Lin, 1999;
Wellman et al., 2001; Resnick, 2002). As a result, researchers have called for a
theoretical and methodological understanding of Internet use that is
multifaceted and acknowledges varied activities, motives, and gratifications
(Shah, Kwak and Holbert, 2001; Bargh and McKenna, 2004; Zhao, 2006).
The extent to which offline interactions that increase social capital are
displaced by online activities that do not is mitigated by two complementary
aspects of Internet use: on one hand, by the novel or enhanced networking
opportunities presented by digital technologies, and on the other hand, by
positive displacement effects whereby offline activities that do not increase
social capital (e.g., watching television) are displaced by online activities
that do (Resnick, 2002; Valenzuela et al., 2009). In this context, online and
offline interactions cannot be assumed to represent mutually exclusive
categories: online interactions may supplement other modes of
communication that maintain social ties and encourage social capital
(Wellman et al., 2001; Quan-Haase et al., 2002; Russell et al., 2008; Vergeer
and Pelzer, 2009), while ties that are initially formed in online contexts
may be continued in offline contexts (Kavanaugh et al., 2005; Best and
Krueger, 2006; Goodsell and Williamson, 2008).
Data from the Pew Internet and American Life Project
Data for this chapter comes from the Pew Internet Project, arguably the
most complete and comprehensive source of data about Internet use in the
U.S. (http://www.pewinternet.org/Static-Pages/About-Us/Project-History.
aspx ). The Pew Project is made up of an ongoing series of nationally
representative telephone surveys of the U.S. population. The Project
fielded its first survey about the general role of the Internet and email in
people’s lives in March 2000. Since that initial survey, the Pew Project has
conducted two to three such surveys each year, each drawing on a new
sample of respondents. In this chapter we combine data from over 50,000
interviews conducted as part of twenty-five different Pew data collection
efforts extending through January 2011.
Trends in Internet use 2000–2011
A primary finding of Witte and Mannon (2010) was that through the first
years of the twenty-first century, there still was a significant digital divide
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72 James Witte, Marissa Kiss and Randy Lynn
in the U.S., particularly with regard to education and income. To set the
stage for this chapter, it is important to consider the most recent data
available to see if this situation has been mitigated or remains the same.
The digital divide based on education and income
Figure 4.1 uses time series data from the Pew Internet and American Life
project to summarize the percentage of U.S. adults who have ever used the
Internet according to each respondent’s highest level of educational
attainment. In March of 2000, 72.4 percent of those with a college degree
said they had used the Internet, as compared to 16.5 percent of those with
less than a high school degree. By January of 2011 these figures had
increased to 94.9 percent and 46.4 percent, respectively. Even using the peak
estimate of Internet use among those with a high school degree, 52.1 percent
from several months earlier, the difference remains over 40.0 percent.
Moreover, as Figure 4.2 shows, when one considers the percentage of
respondents who used the Internet in the day previous to their Pew interview
it appears that the gap according to educational attainment has grown over
time. Seen in this way, the digital divide in the U.S. according to educational
attainment grew from 40.1 percent in 2000 to 52.7 percent in 2010.
100
80
60
College
or higher
Some
college
40
HS grad
Less than
HS
20
0
0
-0
ar
M
1
-0
ar
M
2
M
-0
ar
3
M
-0
ar
4
M
-0
ar
5
M
-0
ar
6
M
-0
ar
7
M
-0
ar
8
M
-0
ar
9
M
-0
ar
0
-1
ar
M
Figure 4.1 U.S. adults who ever used the Internet according to education
(2000–2011)
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The Internet and social inequalities in the U.S. 73
100
80
60
College
or higher
Some
college
40
HS grad
Less than
HS
20
0
0
-0
ar
M
1
-0
ar
M
2
M
-0
ar
3
M
-0
ar
4
M
-0
ar
5
M
-0
ar
6
M
-0
ar
7
M
-0
ar
8
M
-0
ar
9
M
-0
ar
0
-1
ar
M
Figure 4.2 U.S. adults who used the Internet yesterday according to education
(2000–2010)
A similar pattern is seen in Figures 4.3 and 4.4 that illustrate the digital
divide as tied to household income. Beginning in 2000 and continuing
through 2010/2011 there has been a significant gap between individuals in
households with low and high incomes when it comes to those who report
ever having been online (see Figure 4.3) and those who report that they
went online the day before their interview (see Figure 4.4). Clearly in this
regard, the digital divide has not gone away, though it has narrowed:
between 2000 and 2010 the gap in the percentage of individuals in
households with incomes less than $20,000 compared to those in
households with incomes greater than $75,000 has gone from 53.5 percent
to 40.0 percent (see Figure 4.3). However, it is perhaps more important to
consider the percentages of individuals who reported going online on the
day before they were interviewed, as this may be a better measure of the
degree to which the Internet is part of an individual’s everyday life. Seen
in this way, the gap between individuals in households with the lowest
incomes compared to those in households with the highest incomes has
actually grown from 42.0 percent to 46.1 percent between 2000 and 2010
(see Figure 4.4).
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74 James Witte, Marissa Kiss and Randy Lynn
100
80
60
$75,000
or higher
$40,000 $75,000
40
$20,000 $40,000
Under
$20,000
20
0
0
-0
ar
M
1
-0
ar
M
2
-0
ar
M
3
-0
ar
M
4
-0
ar
M
5
-0
ar
M
6
-0
ar
M
7
-0
ar
M
8
-0
ar
M
9
-0
ar
M
0
-1
ar
M
Figure 4.3 U.S. adults who ever used the Internet according to household income
(2000–2010)
100
80
60
$75,000
or higher
$40,000 $75,000
40
$20,000 $40,000
Under
$20,000
20
0
0
-0
ar
M
1
-0
ar
M
2
-0
ar
M
3
-0
ar
M
4
-0
ar
M
5
-0
ar
M
6
-0
ar
M
7
-0
ar
M
8
-0
ar
M
9
-0
ar
M
0
-1
ar
M
Figure 4.4 U.S. Adults who used the Internet yesterday according to household
income (2000–2010)
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The Internet and social inequalities in the U.S. 75
The digital divide based on education and income controlling for other
characteristics
In the previous section we have seen how education and income as
significant aspects of the digital divide were not only manifest in the early
years of the Internet, but continue to leave their mark on Internet use up
through the present. Moreover, as we look at recent data from May 2010,
we see that significant differences in Internet use can also be seen
according to other salient social categories.
This pattern is summarized in Table 4.1, where Columns [a] and [c]
describe, for particular social and demographic characteristics, the
percentage of individuals who have ever used the Internet [a] and the
percentage who reported using it on the day prior to being interviewed [c].
So, for example, the results show that 79.3 percent of men and 78.7 percent
of women have ever used the Internet; however, this small difference is not
statistically significant. Looking at other demographic characteristics, on
the other hand, there are significant differences in percentages according
to age, race and ethnicity.
But these percentages only look at a single demographic characteristic at a
time and may be misleading since the various demographic characteristics are
also related to one another. In an effort to sort this out, logistic regression
results are reported in Columns [b] and [d] of Table 4.1, which provide the
exponentiated log of the odds obtained when ever having used the Internet
and having used it yesterday are regressed on these social and demographic
characteristics. These results indicate that in a multivariate framework, the
significant effects of race and ethnicity fall away, while gender is significant for
having ever used the Internet, but not for having used it yesterday. Age,
education and income, by contrast, are highly significant both for ever having
used the Internet and having used it yesterday. Having established that
differences in Internet use persist in the U.S., it is important to take a closer
look at the consequences of those differences.
Internet use, community type and sources of local information
One aspect of lifestyle that clearly distinguishes non-Internet users from
Internet users is their residential pattern and the type of communities in
which they tend to live. Table 4.2 indicates that non-Internet users are
more likely to have lived in their neighborhoods for a longer time, while a
relatively large proportion of Internet users tend to be relative newcomers
to the neighborhoods they live in. In addition, nearly half of all nonInternet users (44.2 percent) have lived in their neighborhoods for twenty
years or more as compared to under a third of Internet users (30.0
percent). Table 4.2 also shows that non-Internet users tend to live in small
cities, towns and rural areas (72.4 percent), while Internet users live
disproportionately in large cities and suburbs (47.0 percent).
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76 James Witte, Marissa Kiss and Randy Lynn
Table 4.1 Social and demographic patterns of Internet use
Ever used the Internet
Used the Internet yesterday
[a]
percentage
[b]
exponentiated
log of odds
[c]
percentage
[d]
exponentiated
log of odds
Male
79.3
—
62.2
—
Female
78.7
1.611
60.5
1.23
18–24
95.5**
—
77.1**
—
25–34
93.3
0.457*
75.2
0.646*
35–44
87.6
**
0.178
74.1
0.529**
45–54
81.3
0.107**
60.3
0.231**
55–64
75.6
**
0.085
54.7
0.157**
65 and older
42.4
0.018**
29.0
0.074**
White
79.6**
—
61.9**
—
Black
72.4
0.696
55.1
0.863
Asian
91.1
1.097
83.9
1.711
Other/mixed race
79.4
0.992
54.5
0.871
Hispanic
81.4**
1.035
60.5
0.744
Non-Hispanic
78.8
—
61.5
—
Less than HS
51.9**
0.072**
29.8**
0.168**
HS graduate
67.7
0.099
**
48.7
0.262**
Some college
88.0
0.298**
69.2
0.546**
College or higher
95.9
—
82.6
—
Less than $10,000
47.7**
—
30.2**
—
$10,000–$20,000
63.3
—
42.9
—
$20,000–$30,000
73.0
—
52.2
—
$30,000–$40,000
77.6
1.475
53.1
1.33**
$40,000–$50,000
90.2
—
68.9
—
$50,000–$75,000
88.8
—
72.1
—
$75,000–$100,000
94.3
—
83.6
—
$100,000 and above
95.7
—
82.7
—
Gender
**
Age
Race
Ethnicity
Education
Income
**
* p < 0.05, ** p < 0.01. May 2010 Pew Internet and American Life Survey. – indicates
reference category.
1) Constant = 36.586 Nagelkerke Pseudo R2 = 0.487
2) Constant = 3.293 Nagelkerke Pseudo R2 = 0.368
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The Internet and social inequalities in the U.S. 77
Table 4.2 Neighborhood and community characteristics according to Internet use
Never used the Internet (%) Ever used the Internet (%)
How long living in the neighborhood**
Less than one year
5.5
10.4
One to five years
22.6
26.8
Six to ten years
11.6
17.6
Eleven to twenty years
16.1
20.1
Twenty years or more
44.2
30.0
18.7
23.0
8.8
24.0
A small city or town
45.5
35.0
A rural area
26.9
18.0
Type of community **
A large city
A suburb near a large city
* p < 0.05, ** p < 0.01. January 2011 Pew Internet and American Life Survey
It is no surprise that, when compared to Internet users, those who do not
use the Internet are more likely to be long-time residents of small cities
and towns or to live in rural areas, but there are surprising aspects of how
they inhabit their environments. In January 2011, the Pew Project asked a
series of questions about where respondents received information about
their local community. Comparing the upper and lower panels of Table
4.3, there are significant differences between those who have or have never
used the Internet across all three sources of information. Non-Internet
users are more likely to read a print version of a local newspaper every day
(26.2 percent) and to watch a local television news broadcast every day
(64.2 percent) than Internet users, 20.7 percent of whom read a local
newspaper and 45.4 percent of whom watch the local television news every
day. Non-Internet users are also more likely to never read a local
newspaper; thus, local television is their primary source of news.
Interestingly, non-Internet users are significantly less likely to rely on word
of mouth as a source of local information: they are less likely to receive
such information everyday (22.1 percent) than Internet users (25.2
percent), but they are also more likely to never receive local word of mouth
information (16.1 percent) than Internet users (6.7 percent). Thus, it
appears that non-Internet users are already at a disadvantage when it
comes to multiple sources of local information, not just those that are
Internet based.
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78 James Witte, Marissa Kiss and Randy Lynn
Table 4.3 Sources of local information according to Internet use
Source of information (%)
How often do
you get local
information
from…
Print version
of a local
newspaper **
A local
television news
broadcast**
A local radio
broadcast**
Word of mouth
from friends,
family,
co-workers and
neighbors **
Never used the Internet
Every day
26.2
64.2
28.9
22.1
Several times
a week
17.8
17.8
13.2
26.3
Several times
a month
10.7
3.8
6.2
15.8
Less often
12.6
5.7
11.3
19.7
Never
32.7
8.6
40.4
16.1
Total
100.0
100.0
100.0
100.0
Every day
20.7
45.4
34.7
25.2
Several times
a week
18.4
23.1
17.5
32.1
Several times
a month
17.5
9.5
8.7
22.7
Ever used the Internet
Less often
18.0
10.9
13.3
13.2
Never
25.4
11.2
25.8
6.7
Total
100.0
100.0
100.0
100.0
* p < 0.05, ** p < 0.01. January 2011 Pew Internet and American Life Survey
Moreover, as Table 4.4 suggests, Internet users already have a variety of
online resources that they use to obtain particular types of local
information. Column [a] of Table 4.4 indicates that local weather is the
most commonly sought type of local information, as 88.7 percent of all
respondents reported seeking information of this type. Of all those who
sought information on the local weather, Column [b] shows that 43.2
percent used the Internet and/or a mobile device to get this information,
while among those who sought this information and were Internet users
Column [d] reports that 53.9 percent used the Internet and/or a mobile
device to get information on the local weather. Table 4.4 also reveals
interesting variation in the degree to which the Internet and mobile
devices are used for local information according to the type of
information. So, for example, local breaking news is the second most
commonly sought type of local information (Column [a]); however, only
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The Internet and social inequalities in the U.S. 79
Table 4.4 Obtaining local information
Use the Internet or mobile phone to get
information
Individuals who seek information of the
following type:
[a] (%)
% of all
% of Internet
individuals
users only
[b]
[c]
Local weather
88.7
43.2
53.9
Local breaking news
80.0
21.3
26.6
Local politics, campaigns and elections
67.0
26.7
33.9
Local arts and cultural events, such as
concerts, plays, and museum exhibits
60.0
28.4
34.7
Other local government activity, such as
council meetings, hearings or local trials
41.8
15.3
19.2
Local job openings
38.8
44.8
55.7
Local social services that provide
assistance with things like housing, food,
health care, and child care
35.4
19.5
26.7
Local zoning, building and development
30.5
12.8
16.1
January 2011 Pew Internet and American Life Survey. Based on Form B respondents
[N=1,164]
26.6 percent of all Internet users said they used the Internet and/or mobile
devices to get this type of information. By contrast, relatively few
respondents reported looking for information on local job openings 38.8
percent (Column [a]); but, 55.7 percent of Internet users stated that they
used the Internet or mobile devices to get this type of information.
Taken together, the materials found in Tables 4.3 and 4.4 indicate that
as information and communication technology has developed, matured
and become increasingly social and mobile, access to online and offline
local information resources is another way in which lifestyle differences
characterize the digital divide.
Internet use and social ties
As noted above, there has been an ongoing debate about the extent to
which Internet use is likely to increase or decrease the types of social ties
that are associated with social capital. December 2010 data from the Pew
Survey Project speaks directly to this point. All respondents were asked
about their active participation in fourteen different types of groups.
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80 James Witte, Marissa Kiss and Randy Lynn
Results from this question are summarized by the radar graph found in
Figure 4.5, in which the filled-in area shows the percentages of Internet
and non-Internet users who are active in each type of group. For twelve of
the fourteen types of groups, a greater percentage of Internet users than
non-users were active members. Veterans groups or organizations, such as
the American Legion or the Veterans of Foreign Wars, and farm groups
were the only two types of groups in which non-users were more likely to
be active than Internet users. These were also the two types of groups that
attracted the smallest percentages of participants. Overall, the average
Internet user belonged to 2.6 types of groups, while the average non-user
belonged to only 1.3 types of groups.
As is the case with Internet use (see Table 4.1), a variety of social and
demographic factors are associated with participation in different types of
groups and not just whether or not one is an Internet user. Column [a] in
Table 4.5 presents results from Ordinary Least Squares (OLS) regression
of the number of types of local groups, in which an individual is active, on
the same set of demographic and social characteristics that were used as
predictors of the probability of Internet use in Table 4.1. Column [a] of
Table 4.5 shows that women, older individuals, non-Whites (with the
exception of Asians), and those in households with higher incomes belong
to significantly more types of groups. Meanwhile those with less than a
college degree belong to significantly fewer types of groups. In Column
[b] of Table 4.5, the model is expanded to include whether or not an
Internet user
Non-Internet user
Farm
Church
50.00%
Sports or recreation
40.00%
Veterans (e.g. VFW)
30.00%
20.00%
Social or fraternal
10.00%
Consumer
Charitable or
volunteer
0.00%
Youth
Professional or trade
Community/neighborhood
Performance or arts
Literary, discussion
or study
Hobby or club
Parent (e.g. PTA)
Figure 4.5 Participation in social groups: adult Internet users and non-Internet
users in the United States. Source: Pew Internet & American Life
Survey, December 2010.
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The Internet and social inequalities in the U.S. 81
Table 4.5 Active participation in types of groups regressed on demographic
characteristics
Unstandardized regression coefficients
[a]
base model active
group participation
[b]
expanded model
active group
participation
[c]
expanded model all
group participation
—
—
—
Gender
Male
Female
0.271
**
0.251
*
0.139
Age
18–24
—
—
—
25–34
0.003
0.053
0.036
35–44
0.623**
0.709**
0.683*
45–54
0.494**
0.603**
0.807**
55–64
0.618
0.740
**
1.190**
65 and older
0.605**
0.860**
1.555**
**
Race
White
—
Black
0.622
Asian
–0.200
–0.180
0.839
0.838
Other/mixed race
—
**
**
—
0.638
**
0.940**
0.037
**
1.217**
Ethnicity
Hispanic
Non-Hispanic
–0.222
–0.198
–0.079
—
—
—
Education
Less than HS
–1.830**
–1.646**
–2.371**
HS grad
–1.419
**
–1.333
–2.127**
Some college
–0.984**
–0.971**
–1.539**
—
—
—
College or higher
**
Income
0.229**
0.205**
0.254**
0.560**
1.168**
Internet use
Internet user
Non-user
—
—
—
—
Constant
1.568**
1.083**
1.921**
Adjusted R2
0.195
0.200
0.191
* p < 0.05, ** p < 0.01. May 2010 Pew Internet and American Life Survey. – indicates
reference category.
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82 James Witte, Marissa Kiss and Randy Lynn
individual is an Internet user. Adding this variable does little to change
the relationships established in Column [a], while establishing, all other
things being equal, that there is a positive and significant relationship between
Internet use and the number of community oriented groups to which an individual
belongs.
In addition, Pew respondents were asked to consider their active
participation in any other groups, not just those with an obvious
community orientation. When both sets of groups are combined, the
average Internet user participated in a total of 3.9 types of groups as
compared to an average of 2.0 for non-users. Further, as Column [c] of
Table 4.5 indicates this significant difference remains even after
controlling for other individual characteristics, while the effects of these
other characteristics are essentially the same as with the smaller subset of
community groups.
Conclusion
In sum, the theoretical perspectives and empirical analyses presented in
this chapter suggest that despite tremendous changes in the content
available online and the ways that users access content, there has actually
been little change in the fundamental relationship between the Internet
and inequality in the U.S. in recent years. Particularly with regard to
educational attainment and income, there has been no closing of the
digital divide. Further, as the informational resources available through
the Internet have become more valuable, especially with the increase in
fine-grained content that is highly relevant and valuable to specialized
groups, including geographically defined community groups, then the
relative costs and consequences of exclusion increase as well.
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5 Missing in the midst of
abundance
The case of broadband
adoption in Japan1
Mito Akiyoshi
Senshu University
Motohiro Tsuchiya
Keio University
Takako Sano
Ministry of Internal Affairs and Communications
Broadband technology and social and economic outcomes
The advent of broadband technology provides societies with new
communicative opportunities and challenges. The deployment of
broadband is expected to spur economic growth (ITU/UNESCO, 2011). It
is not clear whether or how broadband technology achieves positive
economic and social outcomes, however. In fact, the literature on media
history, the social shaping of science and technology, social constructivism
theories, and Actor Network Theory attest to the complex relationship
between technology and society (Grint and Woolgar, 1997). The growing
field of research on the distribution of access to and use of information
technology is most commonly known under the rubric of digital divide.
Researchers working on the issue of the digital divide rediscover the
coevolution of technology and society, a phenomenon underscored in
research of a constructivist persuasion. Contrary to the initial anticipation
that the Internet would serve as a great social equalizer by democratizing
the production, dissemination, and use of information, it has become
clear that individuals bring different levels of skills and different needs to
the Internet. Instead of democratizing communications, the Internet may
perpetuate or even exacerbate inequality as economic and social returns
to using the Internet differ across the population (van Dijk, 2006; Witte
and Mannon 2010). While the concept of digital divide primarily focuses
on differences between individuals with Internet access and without, it
becomes increasingly evident that social inequality is manifest at the level
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86 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
of different uses among those who have access. The term digital inequality
is often used to turn our attention away from the simplistic dichotomy of
having or not having Internet access to the unequal distribution of various
resources deployed for appropriation of information communication
technology. Digital inequality is becoming a serious issue for research on
social stratification because inequality in digital technology use translates
into inequality in other domains of life. For example, web use is positively
associated with earnings growth by enhancing human capital, by
providing superior access to job information, and by signaling socially
valued aspects of the user’s identity (DiMaggio and Bonikowski, 2008).
The present chapter examines how the propagation of broadband
technology is facilitated or curtailed by the differential distribution of
economic and social opportunities in Japan in order to understand the
dynamics of social stratification processes mediated by the appropriation of
technology. The chapter is organized in six sections. The second section
introduces and motivates the research problem. The third section provides an
overview of key concepts with a special focus on broadband use and social
inequality. The fourth section details the data and methods. The fifth section
presents our findings. By way of conclusion, the sixth section deals with the
relationship between access, skills, and broadband adoption barriers.
Broadband in Japan
Broadband policy development
This section provides an overview of Internet and broadband access in
Japan in order to contextualize and historicize our research problem. The
broadband penetration rate to households in Japan increased around
2001 (see Figure 5.1). In November 2000, the government unveiled its “IT
Basic Strategy” with a goal of making high-speed Internet access (30 to 100
Mbps) available to its citizens by 2005. To implement the strategy, “IT Basic
Law” was enacted in January 2001.
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Figure 5.1 Household Internet penetration rates
Note: As the data format for the year 2006 is different from the one for other years, the data
for 2006 was dropped.
Source: The Ministry of Internal Affairs and Communications of Japan
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Missing in the midst of abundance 87
Services providers were faced with the choice of DSL (Digital Subscriber
Line) or optic fibers. Yahoo! BB, a major Internet service provider
aggressively promoted DSL. NTT (Nippon Telegraph and Telephone), the
privatized former state monopoly, was reluctant to accept DSL requests
from Yahoo! BB and other DSL operators, because it thought that the use
of old coppers for DSL would hinder the deployment of new optic fibers.
Ambivalent, NTT started offering DSL services while accelerating the
deployment of optic fibers (Bleha, 2009; Tsuchiya and Thierer, 2002).2 The
competition between DSL and fiber optics presented a good bargain for
potential customers. By 2009 optic fiber subscriptions surpassed those of
DSL subscriptions (see Figure 5.2). By 2007, Japan boasted “the cheapest
and fastest” broadband services (Orbicom, 2007). Japan’s price for
broadband per megabit per second is the lowest among OECD member
countries (OECD, 2011a) as of September 2011 (see Figure 5.3). In 2010 a
1Mbps connection cost 0.08 dollars in Japan; it cost 0.19 dollars in Korea;
and 1.10 dollars in the United States.
The growth of broadband technology applications in Japan
Three issues are of great interest as to the growth of Internet and
broadband technology applications in Japan. First, Japan started out as an
“underperformer” on Internet connectivity rates during the 1990s and
later it transformed itself into a leader of broadband technology after
2000. Second, much of Japan’s Internet traffic is mediated by the webenabled mobile phone. Third, unlike other industrialized societies, where
gender gaps in computer-based Internet access were present in the 1990s
but disappeared around 2000, the gender gap in computer-based Internet
access persisted in Japan.
25,000,000
FTTH
DSL
CATV
FWA
BWA
20,000,000
15,000,000
10,000,000
0
Sep-05
Nov-05
Jan-06
Mar-06
May-06
Jul-06
Sep-06
Nov-06
Jan-07
Mar-07
May-07
Jul-07
Sep-07
Nov-07
Jan-08
Mar-08
May-08
Jul-08
Sep-08
Nov-08
Jan-09
Mar-09
May-09
Jul-09
Sep-09
Nov-09
Jan-10
Mar-10
May-10
Jul-10
Sep-10
Nov-10
5,000,000
Figure 5.2 Type of broadband subscription in Japan
Source: The Ministry of Internal Affairs and Communications of Japan
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88 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
AQ:
North
or
South
Korea?
Japan
Sweden
Korea
Estonia
Finland
Hungary
France
Slovenia
Canada
Germany
Slovak Republic
Portugal
Poland
Denmark
Austria
United Kingdom
Australia
Czech Republic
Italy
Netherlands
Ireland
Iceland
Switzerland
Belgium
Luxembourg
Turkey
Norway
Spain
United States
Israel
New Zealand
Chile
Greece
Mexico
33.00
19.22
Japan
Sweden
0.21 Korea
1.93
0.28 Estonia
16.34
0.29 Finland
18.16
0.31 Hungary
35.73
0.34 France
5.73
0.38 Slovenia
46.21
0.40 Canada
72.13
0.42 Germany
30.88
0.43 Slovak Republic
21.01
0.46 Portugal
172.57
0.47 Poland
182.00
0.48 Denmark
3.84
0.58 Austria
22.26
0.61 United Kingdom
4.20
0.63 Australia
7.90
0.64 Czech Republic
15.91
0.64 Italy
81.14
0.65 Netherlands
8.89
0.66 Ireland
52.57
0.67 Iceland
6.63
0.70 Switzerland
74.27
0.77 Belgium
40.40
0.78 Luxembourg
11.55
0.89 Turkey
84.76
0.92 Norway
20.66
1.09 Spain
71.70
1.10 United States
71.49
1.39 Israel
28.18
1.56 New Zealand
193.38
1.64 Chile
40.26
1.68 Greece
55.91
4.65 Mexico
41.14
0
1
10
100
1000
Figure 5.3 Broadband prices per megabits per second of advertised speed, Sept.
2011 – USD PPP
Source: OECD (2011a) The OECD broadband portal http://www.oecd.org/dataoecd/22/42/
39574970.xls
From underperformer to leader of broadband adoption
It has been stated that a nation’s Internet connectivity rate or the proportion
of Internet users in the population is mainly explained by its GDP, the
percentage of population with higher education, and quality of existing
telecommunication infrastructure (Norris, 2001). According to these
indices, Japan was an underperformer during the first decade of Internet
diffusion. That is, the actual percentage of Internet users was below what
was predicted by models. In 2000, 34 percent of Japanese households had
access to the Internet while 48 percent of Swedish households and 42
percent of US households were online (OECD, 2011b). The slow diffusion of
the Internet in Japan is attributed to several factors such as limited English
The Digital Divide_BOOK.indb 88
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Missing in the midst of abundance 89
proficiency among the population, the introduction of computer and
QWERTY keyboards without a natural transition from the typewriter, and
exorbitant telephone charges in the days of dial-up.
The IT Basic Strategy was a response to the lagged expansion of Internet
connectivity. It prioritized the provisioning of affordable broadband access.
The expansion of broadband capacity is a chicken-and-egg problem. There
must be strong demand for broadband services to justify investment, but
without services already in operation, it is difficult to create sufficient
demand. The strong commitment combined with coordinated efforts on
the part of the government to update network infrastructure meant that the
initial dilemma was eased by policy measures.
In Japan, fiber optic cable is the leading platform. Fiber-To-The-Home
(FTTH) connections are available among 86.5 percent of households (see
Figure 5.4). Availability of broadband technology does not necessarily
entail actual use, however. The OECD average of broadband subscriptions
per 100 inhabitants was 5.1 in 2011. Japan is ranked sixteenth with 27.0
subscriptions per 100 inhabitants (see Figure 5.5). The striking contrast
between abundant technological capabilities and limited actual use
constitutes the puzzle the present chapter addresses.
Mobile Internet access
Web-enabled mobile phones are widely used in Japan. Akiyoshi and Ono
(2008) observe that mobile phones serve as a viable alternative to computers
for those who have limited resources. The wide acceptance of web-enabled
mobile phones may suppress broadband Internet access from the computer.
There is evidence that there exist mobile phone users who exclusively use
mobile phones to access the Internet (Akiyoshi and Ono, 2008).
100
90
80
70
60
50
40
30
20
10
0
s
y
e en ly ay
n ea lic ge
d ry
d rk es
d
in
pa or ub era lan ma tat anc ed Ita rw land lan pa lan ga man
n
r
e
n n
e
K ep v
S
o
r
i
r
r
S
w
F S
I Hu e
F
N he
Ic
a
R
De ited
G
et
ak ECD
n
N
v
U
o O
l
S
Ja
AQ:
North
or
South
Korea?
Figure 5.4 FTTH/B household availability
Source: OECD (2011a) The OECD broadband portal http://www.oecd.org/dataoecd/47/3/
44435611.xls
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90 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
40
35
Other
Fibre/LAN
Cable
DSL
30
25
20
OECD average
15
10
AQ:
North
or
South
Korea?
5
0
s d k a y e d
y n g
y l c d
le o y
a l ia ia n a ly
a d s n
nd n ar re a c n m n e ur um d n te a nd tri ae n al ai ni a nd e ar ga li n lic hi ic ke
la erla nm Ko orw ran elagdormawedbo elgi ana inla ta Japala us Isr sto str Sp ve It ela eecng rtu pub olapub C ex Tur
r
c
r
o
S
M
E Au
I Gr Hu Po e P e
N F I Kin Ge S em B C F d
he tz e
Sl
Ze A
R
R
x
et i D
te
d
N Sw
ch vak
ew
ni
Lu
te
e
i
N
U
z
o
n
C
U
Sl
Figure 5.5 OECD fixed (wired) broadband subscriptions per 100 inhabitants, by
technology, June 2011
Source: OECD (2011a) The OECD broadband portal http://www.oecd.org/dataoecd/21/35/
39574709.xls
Digital divide in Japan
As is the case with other industrialized societies, Internet access and use
are unevenly distributed across the population in Japan (Akiyoshi and
Ono, 2008). The significance of gender is peculiar to Japan: in other
industrialized societies, the early Internet users tended to be men. By
2000, women caught up with men in terms of Internet use in most
industrialized societies. Figures from as late as the late 2000s show that
gender remains a significant variable in Japan.
Lost in technological bliss? The puzzle
Why does broadband adoption remain suppressed in Japan even as the
essential infrastructure is available in most parts of the country? With its
high-quality broadband infrastructure already in place, the case of Japan’s
broadband adoption or the lack thereof represents the quintessential
challenges faced by industrial societies as they seek to make the most of
new technological opportunities to address a variety of issues including
economic development, education, environmental conservation, social
and health services, and community-building. To anticipate the
conclusion, we found that differences in cultural capital can be carried
over to the digital realm. Those endowed with high levels of cultural
capital are the ones who are willing and able to unlock the potential of
The Digital Divide_BOOK.indb 90
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Missing in the midst of abundance 91
broadband technology. They employ broadband Internet access to do
things they have been doing and to try new types of activities. On the other
hand, those with limited cultural capital are less informed about new
broadband applications. Even when they do use broadband, they tend to
be “univore” users.
Omnivorous use of broadband
Definitions of broadband
In order to identify key determinants that are associated with broadband
adoption, a clear definition of the concept of broadband is required. The
Broadband Commission for Digital Development of ITU/UNESCO
proposes three types of definition: a definition based on quantitative
indicators, a definition based on qualitative indicators, and a definition that
combines quantitative and qualitative indicators (ITU/UNESCO, 2011).
The present chapter adopts the third approach and defines broadband as
connections that have download speeds equal to or faster than 1Mbps
delivered by DSL, cable modem, FTTH/FTTB, satellite, fixed wireless, and
power line communication. As for qualitative indicators, we restrict the
definition of broadband to computer-based connections because computerbased Internet access and mobile phone access differ in affordances.
Becoming a broadband user
Digital technology access is a cumulative and recursive process. The full
process of technology appropriation is achieved when successive kinds of
access are achieved. Van Dijk suggests that in addition to material access,
motivational access and skills access are integral to the process of
technology appropriation (van Dijk, 2006).
Motivational access can be conceptualized as a multistage concept. It
does not always assume a linear order. Sometimes it begins with knowledge
about a particular service followed by interests and intent. Alternatively,
serendipity might have its way and a potential user might stumble on a
product or service that in retrospect, she or he regards essential to
achieving their goals. Social network may matter as well. “Becoming a
broadband user” is an achievement comprised of multiple steps.
Acknowledging the presence of multiple paths that lead to sustained
use and applications, we attempt to examine the distribution of knowledge
about services and applications delivered by broadband. Knowledge may
not initiate the process of technology appropriation but it shapes the
structure of opportunities available to the potential adopter. Knowledge
gaps were identified in European societies in Internet use gaps (Bonfadelli,
2002; van Deursen and van Dijk, 2010). We expect that there exist
substantial knowledge gaps in Japan as well.
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92 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
Usage applications and users
Our inquiry begins with an observation that Japan’s strong broadband
infrastructure in and of itself does not bring about actual use on the part
of its citizens. One of the fruitful approaches to examine a set of variables
that influence the success or failure of a technology is to look into users.
Different types of social groups have different levels of skills and different
preferences for applications (Witte and Mannon, 2010). The present
chapter shows that the classical debates among perspectives on causes and
consequences of inequality are relevant to an understanding of
stratification process in an era in which access to or mastery of new
technologies influences access to jobs, government services, and
opportunities for social and political participation (DiMaggio and
Bonikowski, 2008). Those classical perspectives on social inequality
include the conflict perspective, the cultural perspective, and the
functionalist perspective (Witte and Mannon, 2010).
The conflict perspective explains the existence of social inequality as a
function of class relations. The cultural perspective seeks the origin of
social inequality not only in economic factors, but also in non-economic
ones such as lifestyle, social status, and political power. The functionalist
perspective suggests that observed inequality is a result of a division of
labor, a sine qua non for the functioning of society. A focus on usage
applications and users reveals that sources of digital inequality are
multiple and cannot be reduced to variation in economic resources. As
such, it supports the cultural perspective. As Max Weber analyzed,
distinctive worldviews and lifestyles produce complex systems of
stratification (Weber, 1991; Witte and Mannon, 2010). Specifically,
education and the consumption of “old” media such as TV and books
predict knowledge and use of various broadband applications. Therefore,
the seeming mystery of lack of avid use of broadband technology is
explained by the significance of non-economic resources in technology
use. Availability of affordable broadband technology does not mean the
narrowing of digital inequality or productive use of technology because
technology adoption is a function of cultural resources.
Types of activities supported by broadband technology
A literature review reveals that the Internet has become indispensable to
users in their everyday lives. It is used to help people cope with illness,
pursue training, make financial decisions, look for a new place to live, and
switch jobs. Productive or work-related uses are generally distinguished
from activities associated with entertainment or consumption (DiMaggio
and Bonikowski, 2008). It has been suggested that usage of narrowband
versus broadband connections affect usage time and the type and range of
applications (van Dijk, 2006). Types of application enhanced by broadband
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Missing in the midst of abundance 93
connections include online learning, live streaming, video-on-demand,
and downloading/uploading digital media content.
Omnivorous use
Different levels of skills and different motivations that individuals bring to
the Internet can be conceptualized in terms of cultural capital. It is a
useful notion to deal with subdued use of broadband in a society where
material access is achieved in principle because it calls our attention to
lifestyle differences that are not fully explained by the absence of material
means. Cultural capital refers to cognitive resources, knowledge, tastes,
and dispositions involved in the production and reproduction of class
distinctions. It is supposed to affect labor market outcomes along with
human capital and social capital (Bourdieu, 1984, 1986).
Two issues need to be elaborated on to apply the concept of cultural
capital to analyze differences in adoption and usage of broadband
technology. First of all, it has become increasingly clear that a higher level
of cultural capital is associated with being “omnivorous,” or being able to
consume and enjoy a wide variety of cultural expressions. Bourdieu
suggests a one-to-one correspondence between the level of cultural capital
and the preferred genre of cultural products. He believed that, for
example, the upper class prefers opera and the working class likes popular
music. Nevertheless, empirical studies on cultural consumption repeatedly
found that cultural capital “haves” are more capable of appreciating
multiple genres than cultural capital “have-nots” (Erickson, 1996;
Peterson, 1992; Chan and Goldthorpe, 2007). Those endowed with higher
levels of cultural capital like Stravinsky and Sting while those with limited
cultural capital assets like only Sting. The distinction lies not between
opera lovers and rap fans but between omnivores and univores.
Second, the universe of consumption fields encompasses not only art,
but multiple realms of pursuits such as hobbies, socializing, food, interior
décor, fashion, and media use (Holt, 1998). The roll-out of broadband
implies the emergence of yet another domain where differences in cultural
capital are reflected in differences in interests and activities. Media use is a
domain of cultural practice where habitus, or a collection of patterns of
thought, behavior, and taste is manifested and enacted. Just as those with a
high level of cultural capital enjoy multiple genres of art, they are
omnivorous in media use. In fact, recent studies on Internet use saw the
rise of a “broadband elite” that uses the connection for ten or more online
activities on a typical day (Horrigan and Rainie, 2006).
The slow take-up of broadband technology presents a difficult
conundrum for researchers. The concepts of cultural capital and habitus
can be fruitfully applied to answer why the Japanese do not use broadband
technology when affordable, high-quality access is widely available. The
theoretical answer drawn from the theory of cultural capital is that it is
The Digital Divide_BOOK.indb 93
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94 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
because only those with the right kind of cultural capital and habitus know
enough to use broadband technology for a wide range of online activities.
It is crucial to investigate the link between usage applications and
characteristics of users in terms of the distribution of cultural capital to
examine whether empirical data lends support to the theoretical claim.
Hypotheses
To recap the key concepts and propositions in the previous sections, the
present chapter responds to a call for an approach which would expand
the scope of inquiry beyond material access and would incorporate more
multifaceted aspects of digital inequality. We do so by examining
characteristics of users and actual behaviors rather than speculating about
intrinsic properties of broadband technology. We draw on the theory of
cultural capital to relate different modes of access and uses to different
levels of skill, different motivations and different interests.
We hypothesize that the stagnant adoption rate of broadband
connection in Japan is attributed to the uneven distribution of cultural
capital. Those with limited cultural capital are likely to be unaware of the
availability of new applications even when high-quality broadband
technology is within their reach. When they do know of new applications,
they tend to be univore users. Formally, our hypotheses are as follows:
Hypothesis 1: Those endowed with limited cultural capital resources
are less likely to be aware of new applications delivered by broadband
technology than those with higher levels of cultural capital.
Hypothesis 2: The omnivore/univore distinction is observed in terms
of the number of applications. Those with higher levels of cultural
capital use more applications and services than those with limited
cultural capital assets.
The next section discusses data and methods to test these hypotheses.
Data and methods
Data analysis is made possible by the Broadband Adoption and Usage
Survey (BAUS). The BAUS was designed to address a range of questions
about the socioeconomic characteristics of broadband users and their
online behaviors. The data was collected by an online survey in March
2011. The population of BAUS is individuals with computer-based Internet
access aged between 16 and 65 living in a household in 44 prefectures in
Japan.3 99,684 were randomly chosen from the roster of possible
respondents maintained by a polling organization and invited to take part
in the survey. 3,571 valid observations were obtained. The characteristics
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Missing in the midst of abundance 95
of the respondents were compared with comparable survey data to ensure
that respondents were not significantly different from non-respondents.
Dependent variables
In order to test our hypotheses, we looked at 12 types of broadband
applications (see Table 5.1). Figure 5.6 cross-tabulates types of Internet
and broadband applications with user responses (see Figure 5.6). The
original variables about knowledge of broadband applications have three
categories. We asked the respondent whether she or he (1) knew that a
particular type of application was available and she or he had used it, (2)
knew that the service was available but she or he had never used it, or (3)
did not know that the service was available. Binary variables to indicate
whether the respondent knew about applications were created from these
variables. Those who did not know about availability of a particular
application were coded as one in the new “don’t know” variable.
Independent variables
Key variables that are known to affect usage patterns are included in the
models. Female is a binary variable. Age is a continuous variable. Indicator
variables were used to code the level of education, hours spent watching
TV on a typical day, the number of books the respondents read per month,
marital status, employment status and living with a child. Education, the
number of hours spent watching TV, and the number of books read were
treated as proxies of cultural capital.
Table 5.1 Types of broadband application
Types of application
Observed variables
Education
Online learning
Transaction
Transactions with government agencies
Video streaming
Diet and local assembly sessions
Press conferences
Stock-holder meetings
Medical services
Making a medical appointment
Seeking health advice online
Consumption
Grocery shopping
Auctioning
Entertainment
Downloading music
Downloading novels
Video on demand
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96 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
Known and ever tried
Known but never tried
0%
E-learning
20%
14.5%
General stockholders’ meeting (viewing 2.5%
a general stockholders’ meeting)
7.8%
The diet (viewing the diet)
5.6%
Processing transactions with goverment
agencies online
9.0%
Health (medical consulting services)
Music (listening, downloading
the music)
Fiction (novel and comic downloading)
Auction (purchasing food and sundries)
80% 100%
60.8%
24.7%
63.1%
37.7%
54.5%
37.3%
57.1%
47.5%
Grocery (purchasing food and sundries)
Doctor (making an appointment
for medical treatment)
Unknown
60%
34.4%
Press conference (viewing a
press conference)
Video-viewing (video on
demand downloading)
40%
43.6%
60.4%
28.8%
32.5%
57.4%
13.0%
41.7%
5.9%
57.2%
40.7%
14.5%
13.8%
45.3%
36.9%
49.7%
9.6%
14.7%
70.8%
49.2%
7.1%
42.7%
8.1%
Figure 5.6 Internet and broadband applications
Source: BAUS
Findings
A series of indicator variables to distinguish those who did not know about
services were created to test Hypothesis 1. By regressing “don’t know”
variables on independent variables, their influence and statistical
significance were estimated. The results of logistic regression are
summarized in Table 5.2. The dependent variable was coded as one if the
respondent did not know about an application. A negative sign suggests
that the pertinent independent variable suppresses the log odds of being
ignorant of an application. For example, the positive and significant effect
of being female in Model 2 (0.471) indicates that women are 1.6 (=e0.471)
times as likely as men to state that they don’t know that they can use the
computer to complete transactions with government agencies.
In addition to proxies of cultural capital, other “usual suspects”
variables show interesting patterns. Gender turned out to be significant in
6 applications out of 12. Those include transactions with government
agencies, viewing information about diet and local assembly sessions,
The Digital Divide_BOOK.indb 96
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The Digital Divide_BOOK.indb 97
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TV
0.0398
(0.8672)
0.0182
(0.9362)
0.0136
(0.9529)
0.0618
(0.7868)
< one hour
< two
hours
< three
hours
three or
more
hours
–0.616***
(0.0000)
–0.207*
(0.0380)
Education Junior
college
University
0.150
(0.1007)
Female
–0.336***
(0.0001)
–0.394***
(0.0000)
0.0785
(0.6886)
–0.127
(0.5188)
0.106
(0.5836)
–0.0796
(0.6869)
–0.173
(0.3820)
–0.212
(0.2757)
–0.305
(0.1319)
–0.251**
(0.0077)
–0.200*
(0.0292)
–0.0398
(0.8443)
0.701***
(0.0000)
0.471***
(0.0000)
(1) learning (2) transaction (3) diet
–0.291**
(0.0029)
0.580***
(0.0000)
–0.198*
(0.0286)
0.0266
(0.7323)
0.322
(0.0956)
0.272
(0.1622)
0.218
(0.2519)
0.135
(0.4982)
–0.0136
(0.9467)
–0.0768
(0.7067)
–0.0704
(0.7254)
–0.120
(0.5661)
–0.265
(0.1670)
–0.290
(0.1336)
–0.204
(0.2824)
–0.195
(0.3240)
–0.355*** –0.408*** –0.344***
(0.0000) (0.0000) (0.0000)
–0.159
(0.0863)
0.613***
(0.0000)
–0.371
(0.0547)
–0.374
(0.0550)
–0.153
(0.4214)
–0.288
(0.1493)
–0.184*
(0.0355)
–0.126
(0.1746)
–0.0737
(0.3589)
(4) press
(5)
(6)
(7) advice
conference stock-holder appointment
meeting
Table 5.2 Logistic regression models predicting don’t know responses
0.152
(0.2560)
–0.505
(0.0575)
–0.796**
(0.0041)
–0.866**
(0.0015)
–0.852**
(0.0032)
–0.867**
(0.0022)
–0.788**
(0.0076)
–0.776**
(0.0099)
–0.617*
(0.0304)
–0.563*
(0.0409)
–0.0416
(0.7705)
–0.473
(0.0947)
0.0438
(0.7749)
0.00889 –0.0876
(0.9562) (0.5583)
0.0482
(0.7330)
–0.305
–0.437
(0.3006) (0.1330)
–0.177
(0.2752)
–0.186
(0.2920)
–0.169
(0.2581)
–0.530*
(0.0303)
–0.637*
(0.0107)
–0.503*
(0.0390)
–0.318
(0.2138)
–0.100
(0.4036)
–0.0733
(0.5505)
0.368***
(0.0010)
(8) grocery (9) auction (10) music (11) novel
–0.372
(0.1514)
–0.451
(0.0886)
–0.184
(0.4722)
–0.00994
(0.9702)
–0.0712
(0.5639)
–0.0502
(0.6927)
0.321**
(0.0051)
(12) video
on demand
The Digital Divide_BOOK.indb 98
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–0.716***
(0.0001)
–0.234***
(0.0000)
five or
more
books
Household income
3571
3571
–0.194*** –0.199*** –0.218*** –0.175***
(0.0000) (0.0000) (0.0000) (0.0000)
–0.184***
(0.0000)
3571
–0.591*** –0.584*** –0.725*** –0.418***
(0.0000) (0.0000) (0.0000) (0.0027)
–0.952***
(0.0000)
3571
–0.623*** –0.573*** –0.589*** –0.632***
(0.0000) (0.0000) (0.0000) (0.0000)
–0.697***
(0.0000)
3571
–0.481*** –0.424*** –0.436*** –0.406***
(0.0000) (0.0000) (0.0000) (0.0000)
–0.485***
(0.0000)
3571
3571
–0.176*** –0.235***
(0.0000) (0.0009)
–0.693*** –0.991**
(0.0000) (0.0029)
–0.699*** –0.344
(0.0000) (0.1926)
(12) video
on demand
3571
–0.180**
(0.0069)
–0.403
(0.1029)
–0.651*
(0.0139)
3571
–0.139*
(0.0284)
–0.426
(0.0757)
–0.543*
(0.0276)
3571
–0.158**
(0.0030)
–0.631**
(0.0022)
–0.834***
(0.0001)
3571
–0.215***
(0.0001)
–0.528*
(0.0109)
–0.757***
(0.0005)
–0.692*** –0.548*** –0.646*** –0.682***
(0.0000) (0.0000) (0.0000) (0.0000)
(8) grocery (9) auction (10) music (11) novel
–0.529*** –0.587***
(0.0000) (0.0001)
(4) press
(5)
(6)
(7) advice
conference stock-holder appointment
meeting
P-values in parentheses.
* p < 0.05 ** p < 0.01 *** p < 0.001
Notes: Employment status, age, network size, mobile phone ownership, marital status and living with a child are controlled. Coefficients for the controls are now
shown. The reference category for education is high school or less, the reference category for TV is zero, and the reference category for the number of books is zero.
3571
–0.736***
(0.0000)
< five
books
N
–0.520***
(0.0000)
< three
books
Books
(1) learning (2) transaction (3) diet
Table 5.2 continued
Missing in the midst of abundance 99
viewing press conferences, viewing stockholder meetings, downloading
novels and comics, and video viewing including on-demand services. On
the other hand, there are no gender differences in knowledge about
online learning, grocery shopping, making an appointment for medical
treatment, medical consulting, downloading music, and auctioning.
Rather than having uniform effects, the effect of gender varies across
types of application. It is beyond the scope of the present chapter to
determine what produces observed differential effects, but it seems that
the effect of gender is insignificant in activities traditionally popular
among women (e.g. learning and grocery shopping). Further research is
needed to examine the effect of gender in terms of the relevance of an
application.
Household income has negative effects on the log odds in all models.
Negative signs suggest that those who are in affluent households are likely
to know about a wide variety of applications. Even though shopping and
auctioning are common applications used by the majority of the
respondents (see Figure 5.6), the sizable effects of household income on
these two dependent variables suggest that there exist households that are
deficient not only in disposable income but also in knowledge of online
shopping. Unlike gender, household income is significant in all the
models. The unequal access to and use of information and communication
technology may not be a distinct or new type of inequality. Rather, the
results suggest that it is closely related to traditional inequality issues such
as unequal distribution of household incomes.
At the same time, variables associated with the level of cultural capital
have remarkable effects. The adoption of broadband technology cannot
be reduced to economic difference. As for institutionalized forms of
cultural capital, the indicator for junior college or for vocational school is
significant in five models. The indicator for university or for four-year
college is significant in seven models. Interestingly, the two education
indicators are not significant in models regarding consumption and
entertainment. It implies that education makes differences in more
consequential areas of activity. In particular, the effect of university-level
education on online learning is remarkable. Those with university degrees
are the first to know about online learning opportunities.
In summary, our first hypothesis is supported by data. Those endowed
with limited cultural resources are less likely to be aware of new
applications delivered by broadband technology than those with higher
levels of cultural capital. Differential use practices are produced by
different levels of cultural capital as well as by socioeconomic status and
demographic attributes.
To test Hypothesis 2, a zero-inflated Poisson (ZIP) model is constructed.
The dependent variable is the number of applications known and tried by the
respondents. It is constructed by adding up the values of indicators for
knowing and having used applications. Because there are 12 applications, the
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100 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
maximum possible value is 12 and the minimum is 0. All the independent
variables used in logistic regression analysis are included in the model.
Contrary to logistic regression models regarding the lack of knowledge, a
positive coefficient in the current ZIP model indicates that it is positively
associated with the number of applications (see Table 5.3). The first set of
coefficients refers to the Poisson model for those who have used at least one
application. The second set of coefficients refers to the binary model to classify
the individual into either the “always zero” group or the “not always zero” group.
Table 5.3 Zero-inflated poisson regression predicting the number of applications
ever used
(a) Count Equation
Female
(b) Binary Equation
–0.0500
(0.0564)
Education Junior college 0.0804 **
(0.0098)
TV
Books
University
0.107***
(0.0002)
< one hour
–0.00165
(0.9789)
< two hours
–0.0783
(0.1939)
Female
–0.328 *
(0.0407)
Education Junior college
–0.171
(0.3900)
University
–0.0646
(0.6964)
< one hour
0.262
(0.4099)
< two hours
–0.0296
(0.9249)
< three hours –0.0313
(0.6107)
< three hours
–0.0229
(0.9441)
three or more –0.0800
hours
(0.1967)
three or more
hours
–0.426
(0.2233)
< three books
–0.336 *
(0.0319)
< three books 0.169 ***
(0.0000)
TV
Books
< five books
0.216 ***
(0.0000)
< five books
–0.300
(0.2680)
five or more
books
0.221***
(0.0000)
five or more
books
–0.232
(0.4012)
Household income
0.0689 ***
(0.0000)
Household income
N
–0.174 *
(0.0211)
3571
P-values in parentheses.
* p < 0.05 ** p < 0.01 *** p < 0.001
Notes: Employment status, age, network size, mobile phone ownership, marital status, and
living with a child are controlled. Coefficients for the controls are now shown. The
reference category for education is high school of less, the reference category for TV is zero,
and the reference category for the number of books is zero.
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Missing in the midst of abundance 101
The result is consistent with our hypothesis that the omnivore/univore
distinction is observed in terms of the number of applications. Education
and the number of books read are positively associated with the number of
applications ever used. The highly educated and the well-read are likely to
try different applications. Household income has a positive influence on
the number of applications as well. On the other hand, cultural capital
proxies are not significant in the bottom half of the output. Cultural
capital proxies do not change the odds of being in the always zero group
compared with the not always zero group.
To summarize, data analysis confirmed that our hypotheses are
supported. They together suggest that usage applications are systematically
related to cultural capital assets. Holding socioeconomic conditions and
demographic attributes constant, those endowed with higher levels of
cultural capital are likely to know about available broadband applications
and are likely to try some of them. Our analysis also supports the
omnivore/univore distinction. These findings are interesting for two
reasons: (1) they show that patterns of broadband applications are
successfully analyzed in terms of the production of distinction (in
Bourdieu’s sense); and (2) they reveal that there are strong connections
among seemingly unrelated individual traits and activities (reading books
and auctioning online, for example).
Conclusion
The present chapter has raised a number of intriguing questions about
what explains the sub-optimal use of broadband capability in Japan. It
employs the cultural perspective to uncover the roots of inequality in
Internet use. As it turned out, successful usage presupposes not only
material access, but motivational access and knowledge. Basic digital and
informational skills such as touch typing and using a search engine are
relevant. Yet the challenge of effective broadband adoption and usage
cannot be trivialized to the issue of technology per se. Our analysis shows
that traditional inequality issues are of much importance. Drawing on the
concept of omnivore derived from the critique of Bourdieu’s theory, we
demonstrated that individuals rich in cultural capital use a wide variety of
broadband applications. Some individuals are excluded from newly
emerging communicative possibilities by choice or by circumstance not
because they do not have access to a computer, but rather because they do
not have the right cultural tools. Socioeconomic factors and demographic
characteristics remain influential as well.
The first and foremost contribution of the present chapter is to address
the serious omission of current research on broadband adoption and
application, namely, the lack of conceptual elaboration, definition, and
theory. It began with simple yet central questions such as what exactly
having access to broadband Internet is and who are likely to be unaware of
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102 Mito Akiyoshi, Motohiro Tsuchiya and Takako Sano
available broadband applications. Drawing on the classical sociological
traditions of cultural perspectives (Weberian theory) in general and
cultural capital in particular, it identifies multiple paths through which
differences in cultural capital translate into differences in use and
application. Second, the chapter empirically examines socioeconomic and
behavioral variables and mechanisms involved in broadband adoption in
under-studied communities of broadband users. Japan is among the
leaders of broadband deployment in the world. Detailed analyses of
broadband adoption patterns have been much needed but yet they have
been hard to come by thus far partly because of the lack of data. The
present chapter is a first step to fill in the lacuna in our knowledge with
newly available data.
References
Akiyoshi, M. and Ono, H. (2008). The diffusion of mobile Internet in Japan. The
Information Society, 24(5), 292–303.
Bleha, T. (2009). Overtaken on the Information Superhighway: How the U.S. lost Internet
leadership and what to do about it. Charleston, SC, US: Booksurge.
Bonfadelli, H. (2002). The Internet and knowledge gaps. European Journal of
Communication, 17(1), 65–84.
Bourdieu, P. (1984). Distinction : A social critique of the judgment of taste. Cambridge,
MA, US: Harvard University Press.
Bourdieu, P. (1986). The forms of capital, (R. Nice, trans.). In J. G. Richardson
(ed.) Handbook of theory and research for the sociology of education (241–258). New
York: Greenwood Press.
Chan, T.K. and Goldthorpe, J.H. (2007). Social Status and Newspaper Readership.
American Journal of Sociology, 112(4), 1095–1134.
DiMaggio, P. and Bonikowski, B. (2008). Make money surfing the web? The impact
of Internet use on the earnings of US workers. American Sociological Review,
73(2), 227–250.
Erickson, B. (1996). Culture, class, and connections. American Journal of Sociology,
102(1), 217–251.
Grint, K. and Woolgar, S. (1997). The machine at work: Technology, work and
organization. Cambridge, UK: Polity.
Holt, D. B. (1998). Does cultural capital structure American consumption? Journal
of Consumer Research, 25(1), 1–25.
Horrigan, J. B. and Rainie, L. (2006). The Internet’s growing role in life’s major
moments. Pew Internet and American Life Project, Washington, DC. Retrieved
August 5, 2011. http://www.pewinternet.org/Reports/2006/The-InternetsGrowing-Role-in-Lifes-Major-Moments.aspx
ITU/UNESCO. (2011). Broadband: A platform for progress. Retrieved October
23, 2012 from http://www.unesco.org/new/fileadmin/MULTIMEDIA/HQ/
CI/CI/pdf/broadband_commission_report_overview.pdf
Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet
worldwide. Cambridge, UK: Cambridge University Press.
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Missing in the midst of abundance 103
OECD. (2011a). Broadband Portal. Retrieved August 5, 2011 from http://www.
oecd.org/document/54/0,3746,en_2649_34225_38690102_1_1_1_1,00.html
OECD. (2011b). OECD Telecommunications and Internet Statistics, (database).
Retrieved August 5, 2011 from http://www.oecd-ilibrary.org/science-andtechnology/data/oecd-telecommunications-and-internet-statistics_data-00170-en
Orbicom. (2007). Digital Review of Asia Pacific 2007/2008. Ottawa, Canada: IDRC.
Peterson, R. A. (1992). Understanding audience segmentation: From elite and
mass to omnivore and univore. Poetics, 21(4), 243–258.
Tsuchiya, M. and A. Thierer. (2002). Is America exporting misguided
telecommunications policy? The U.S.-Japan Telecom Trade Negotiations and
beyond. CATO Institute Briefing Papers, 79.
van Deursen, A. J. A. and van Dijk, J. A. G. (2010). Internet skills and the digital
divide. New Media & Society, 13(6), 893–911.
van Dijk, J. A. G. M. (2006). Digital divide research, achievements and
shortcomings. Poetics, 34(4–5), 221–235.
Weber, M. (1991). From Max Weber: Essays in sociology, London: Routledge.
Witte, J. C. and Mannon, S. E. (2010). The Internet and social inequalities. New York:
Routledge.
Notes
1 An earlier version of this chapter appeared as a presentation at TPRC 2011
(Arlington, VA, US on September 24, 2011). The first two authors are grateful
to the Institute for Information and Communication Policy for financial
support. We also received helpful advice from Massimo Ragnedda and Glenn
Muschert, the editors of this volume.
2 NTT was also reluctant to open up optic fiber facilities, because the fiber
networks were, NTT claimed, established after its privatization in 1985 and
thus it had proprietary rights over them. NTT’s bifacial approach (responding
to DSL requests and deploying optic fibers) enabled a swift transition to
broadband technology.
3 Originally, BAUS was designed to include a nationally representative sample.
One day prior to the scheduled survey start date, the Great Eastern Earthquake
struck Japan. The survey was suspended and was eventually conducted a few
weeks later dropping four hardest-hit prefectures, namely, Ibaraki, Iwate,
Miyagi, and Fukushima.
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Section 3
Rapidly developing large
nations – the BRIC nations
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6 The digital divide in Brazil
Conceptual, research and
policy challenges
Bernardo Sorj
Edelstein Center for Social Research
Introduction
The digital divide refers to the social consequences of the unequal
distribution of access and users’ capabilities of information and
communication technologies among countries and within societies. In this
article we discuss some theoretical, research and policy challenges posed
by the digital divide within national societies, that is, how the different
levels of access to products, services, and benefits of new information and
communication technologies affects different segments of the population.
The Brazilian case will be used to exemplify the general argument.
Communication and information technologies (C&IT) include an
array of products (radio, TV, cable TV, fixed and mobile phones,
computers, the Internet) and, although they are converging technologies,
each one of them creates its own digital divide. In this study we will focus
mainly on the digital divide related to the unequal access to computers
with Internet connection (telematics).
From a sociological perspective, the main theoretical question posed by
the digital divide is how it is related to and affects existing forms of social
stratification. To answer this question social scientists need to clearly
conceptualize the issues involved and to produce or have access to data
that can inform theoretical efforts. From a policy perspective the
challenge is to ensure that telematics diminish rather than increase social
inequality.
Social stratification and the Internet
Classical sociological theories on stratification are a necessary, but limited,
starting point to understand how the Internet is disseminated and used.
Marxist theories can be extremely useful to understand the capital
accumulation dynamics and the formation of dominant groups in the
communications sector, but are rather unhelpful for the understanding of
how they disseminate and impact society, other than the general
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108 Bernardo Sorj
statement, which is not rigorously Marxist, that the richer have more and
better access (at home, work and school) than the poorer.
Weberian theory of social status is relevant to the extent that there is a
strong correlation between level of education and the capacity to
transform Internet information into knowledge. However, Weber’s concept
of status, while it includes education, is much broader. Finally, the
Durkheimian concept of division of labor could be developed to explain
changes in the labor market structure (job creation and destruction, job
qualifications) produced by telematics, but is less insightful regarding the
ways by which new technologies disseminate among different social strata.
In the preceding decades conceptual debates in sociology shifted their
focus. The most important change was toward the analysis of global forms
of stratification instead of national forms. While national studies are more
sensitive to the symbolic and political dimensions of social classes,
globalization theories tend to have a narrower economic perspective. This
is a natural result of the level of abstraction needed to generalize about
global trends. The paradoxical effect is that sociological research, even
when intended to be critical of dominant trends, tends to converge with
the dominance of economic thinking on social stratification. This not only
applies to the digital divide but in general studies on social stratification
become strongly influenced by economics and policy making, which is
translated in focusing mainly on the issues of social inequality and poverty.
In fact a great number of academic studies and, even more, reports on
the digital divide made by international bodies which command enormous
resources and research capabilities are mostly made by economists or
strongly influenced by the economic perspective. For sociologists the best
source for data on social trends in telematics would be that of research
firms serving major telecom communication, but their data is not publicly
available.
Understanding the impact of the Internet in social stratification is
therefore a complex and still unresolved question. The problem obviously
surpasses the specificities of the impact of the Internet on society, which
we will describe, and is related to general changes in late capitalism.
Classical theories of stratification were developed in Europe, before the
welfare state, economies of mass consumption, and service-based
economies. From Marx to Bourdieu, theories of social stratification were
conceived in European societies in which social classes were relatively selfcontained subcultures, from taste to politics. This is no longer the case,
even in Europe, and was always less so in the USA and many other nations
like, for instance, Brazil. Given the strong influence of the economic
perspective on the debates on the digital divide, sociologists can at least
contribute by qualifying the issues, by analyzing the social dimensions of
telematics impact on different social groups, while working on reshaping
the problems and concepts posed by classical theories of social
stratification.
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The digital divide in Brazil 109
What are the specific characteristics of the Internet’s impact on social
stratification? Social stratification refers to individuals’ relative position
in society within a continuum distributed according to criteria of higher
or lower access to economic, political or symbolic resources. The digital
divide, in principle, is not a continuum but a binary distribution of the
population between those who have (access) and those who have not,1
although this opposition masks the enormous variation among those
that have access – in particular quality and time of access and the
capacity to make the best use of the possibilities of the media, mainly
dependent on the educational qualifications of the users (see Witte and
Mannon, 2010).
Telematics also represents a tool that enhances previous social networks
and social capital. The more diversified the number and quality of
professional contacts the higher the potential of the Internet as a medium
to enhance professional and work opportunities. Therefore its potential as
a communication instrument is greater among high income users since
most probably all the members of their network have access to the Internet,
while this is not the case for the low-income users. This is even truer in the
case of international contacts, because low-income sectors are very
unlikely to have an international social network (with the relevant
exception of poor families with members working abroad, often illegally,
for whom the Internet offers cheap communication and contact with their
native land and families).
One of the characteristics that make the relationship between the
digital divide and other forms of stratification particularly elusive is the
poly-functional character of the Internet. Access doesn´t indicate the type
of uses. It can be used for leisure and amusement, as a communication
tool, a source of information, an instrument for access to knowledge or
part of a job definition. Therefore having Internet access and knowing the
basics of computing does not necessarily mean that it enhances people’s
life chances. It is the uses of information technology that are the most
important criterion for evaluating its impact on social structures. These
uses depend on the capabilities and creative appropriation of the new
technology by the different social actors.
While there are correlations between having access and level of income,
literacy is a sine qua non precondition for using the Internet. The “old”
communication technologies (phone, radio, TV) are part of the family of
“illiterate friendly” products – that is, products that can be used by
individuals who have little or no literacy – while computers and the
Internet not only demand basic educational skills but their relevance and
potential increase in direct proportion to previous intellectual skills.2
Differently from other forms of stratification, telematics has decisive
generational determinants: the older the person the higher the chances of
having difficulties to adapt to the use and possibilities of the new
technologies.3
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110 Bernardo Sorj
As the Internet is spreading very rapidly, the digital divide should be
analyzed in a diachronic and dynamic perspective, as a case of the
social product cycle, in which initially a product is introduced in small
quantities with a high price and later it is mass-produced permitting
access by a large part of the population. A new product initially reaches
only those at the highest income levels and later, with mass production
and price reduction, is disseminated throughout all sectors of the
population. Thus, the dynamics of technological innovation always
reinforce social inequality in the initial stages, when the product
reaches only the highest income sectors of the population. At a later
stage of mass production, the product is disseminated through the
lower social classes in a process that can be more strongly affected by
public policy.
Since richer sectors of society are the first to have access to new
products, they have the benefit of initial competitive advantage in using
and mastering them. At the same time, those who are excluded face new
disadvantages. Therefore new ICT products increase, in principle, the
social gap and social exclusion. Therefore, as we will see below, the main
aim of digital inclusion policies is to diminish the negative impact of new
ICTs on wealth distribution and life chances.
The digital divide in Brazil
Existing data on Brazil’s digital divide is quite sophisticated. Still, it hardly
allows for a more detailed sociological analysis.4 Nonetheless, what do the
existing data show (the latest being from 2010)?
1) Access is distributed unequally among regions. The poorer the region
the lower the percentage of people with Internet access at home. The
North and the Northeast regions, the poorest of the country, have,
respectively, 17 percent and 15 percent of homes with Internet access,
while the Southeast has 39 percent and the South 32 percent.
2) Access is related not only to income, but geographical location. While
the urban areas’ national average is 31 percent, the rural areas’
average is 6 percent, with a slower rate of growth. Although the rural
population is poorer than the urban, the enormous difference
between them is due to the fact that a large number of rural areas have
no access to Internet servers. Therefore regional differences are also
related to the fact that the poorest regions also have the highest
percentage of the rural population. For private telecom enterprises
serving sparse populations is not profitable and universalization of
infrastructure access depends on public policies that subsidize or
make mandatory connecting all parts of the territory. In spite of the
Brazilian government’s plans to make service universal, the goal is still
far from being achieved.
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The digital divide in Brazil 111
3)The growth of households with Internet access did increase
exponentially in recent years. It went from a national average of 13
percent in 2005 to 31 percent in 2010. Price reduction for computers,
with government tax exemptions for the cheapest models,
undoubtedly played an important role, but for the poorer groups the
major bottleneck is the high monthly cost of subscribing to Internet
services or phone bills.
4) A division of the population in five classes of strata 5 (A, B, C, D, E)
shows 90 percent of the highest strata had Internet access in 2010,
compared to 65 percent of group B, 24 percent of group C, and 3
percent of groups D and E. While the growth in the number of persons
with access from group A remained stagnant in recent years, having
arrived at the near saturation point, the most important growth
happened in group C.
5) Access to broadband Internet is also distributed unequally between
social classes and regions, although it tends to increase in all of them.
6) If we include other forms of access (work, LAN-houses, houses of other
people, and school) the number of persons with Internet access in
total went from 30 percent in 2005 to 49 percent in 2009. The
percentage of the population using LAN-houses for Internet access
increased from 18 percent in 2005 to 34 percent in 2010, indicating
that for the poorest strata LAN-houses are a main source of access and
are responsible for an important part of the growth of Internet access
for this group.6 Twenty-seven percent cited the houses of others as
their main source of access, which confirms our own research that,
among the poor, houses of friends or family are a central source of
access (see Sorj and Guedes, 2005). Work was also indicated by 22
percent as the main site of access, which probably follows the same
pattern of being an alternative for those that do not have access at
home. School was indicated by 14 percent as being the main source of
access, a number that should grow with the expected increase of
technology labs in public schools, still poorly served (see Sorj and
Lissovsky, 2010). Finally, free public access in LAN-houses represented
4 percent.
7) Communication is the most important Internet activity (94 percent),
followed by searches for information (87 percent) and education (66
percent), with only 17 percent using it for financial services.
Participation in blogs, discussion lists and Twitter is higher among the
richer, the most educated, the younger, and in the wealthier regions.
8) The use of the Internet through mobile phone is only relatively
widespread among class A (21 percent), decreasing to 10 percent in
class B, 5 percent in class C and 1 percent in classes D/E.
The findings presented above mainly confirm general trends observed in
developing countries. Still they have limited relevance for understanding
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112 Bernardo Sorj
the relative importance of the Internet in life quality and life chances for
different social groups: how e-literacy (or the lack of it) affects the labor
market, job opportunities, social mobility, job searches, income,
consumption, access to relevant information, social participation and news
of the world. In this sense more sociological research is needed, in
particular comparative case studies that focus on particular social groups
and environments (work, school, job qualifications/salary, school, etc.).
This is not a task easy to quantify. For instance, quantifying the impact of
telematics on children’s school performance among different social
backgrounds is far from obvious if we consider that there is no clear
consensus on the impact of telematics on education in general.7
Statistical studies – in particular those on developing countries – have a
central parameter: the division between those who have and those who do
not have access to computers and to the Internet. Although central, this
measurement is insufficient to understand the different processes of social
appropriation by the actor: the capacity for making sense, interpreting and
using the information available on the Internet, both by individuals and
communities. Case studies are extremely useful but mostly they refer to
exceptions rather than rules.8 More qualitative and quantitative study is
needed on the relationship between content production and content
appropriation among the different sectors of society.
It is important to differentiate between the social impact of new
technologies as presented in statistical data and the concrete way that
those technologies are experienced by the users. Personal affect does not
figure in aggregate data or theoretical concepts, but is based on
comparing their current with their previous situation. In the case of the
digital divide, the experience in Brazil and other developed countries is
that the widespread dissemination of mobile phones made it possible for a
large proportion of the population to have access, for the first time, to a
phone line, in spite of use limitations from difficulty to pay mobile fees. In
addition, many case studies indicate that the use of telematics improves
the quality of life of poor communities. This may be the case, but it does
not mean that social inequality is decreasing, considering the
appropriation of the new technologies by the dominant groups of society
who generally have more access and superior skills to use digital
technologies, compared with less affluent groups.
Digital divide policies
Social stratification, and in particular social inequality, cannot be
dissociated in contemporary capitalism from the role of the state. Either
through legislative and regulatory measures, or by distributive public
policies, state intervention affects income and access to public goods;
influencing social inequality and the life conditions of the poorest sectors
of the population. Both in academic research and policy reports, the
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The digital divide in Brazil 113
relationship between the Internet and social stratification has as its main
focus its impact on social inequality and poverty. However poverty is not an
objective category. It is defined by common sense and/or political fiat, and
it changes according to the level of cultural/economic/technological/
political development of each society. The introduction of a new category
of products for consumption that become a condition of “civilized” life (be
it a telephone, electricity, a refrigerator, radio or TV) raises the minimum
standard of living which defines poverty.
Although many authors and policy think tanks present the new
communication technologies as a panacea, the introduction of new
“essential” products tend to increase inequality and feelings of social
deprivation (see Sorj, 2005). Policies related to reducing the digital divide
as a tool in the fight against poverty, do not necessarily diminish social
inequality or change existing forms of social stratification. Furthermore,
under conditions of economic growth it is possible to reduce poverty
indicators (the size of the population below a set poverty line), while
simultaneously increasing social inequality. Thus the fights against
inequality and poverty have some convergences but are not synonymous.
Internet access is now considered a public social good in most countries
and public policies include, inter alia, assuring that access is available to
the more isolated regions, distributing laptops to students, tax exemptions
to diminish the cost of computers, creating computer labs at public schools
and opening free access LAN-houses.
The search for miraculous solutions to solve social problems is a
constant in developing countries. The Internet is too important to be
brought into the cycle of miracle cures that later are abandoned for not
meeting unrealistic expectations. Policies aimed at reducing the digital
divide are a necessary component of social policy but they are an
insufficient answer to social and economic problems. The same is true in
relation to e-education and to the problems of school performance.
Social policies related to the digital divide cannot be dissociated from
education policies. The ability to use the information available on the
Internet as a source of knowledge, and intellectual and professional
development depends on the users’ prior skills. This qualification assumes
basic literacy and abilities acquired within the school system. Thus social
inequality as expressed in educational inequity is reproduced and
increases with use of the Internet. As long as much of the population of
the developing world continues to struggle with illiteracy and semi-literacy,
universal access to the Internet will be an illusory goal.
Training in the use of the computer and the Internet (called digital literacy
or e-literacy) can be offered through formal courses in school or at work,
private courses, or courses promoted by non-governmental organizations, or
in contexts (schools, work or home) where the Internet is used and people
nearby are able to offer assistance when needed. Children, in particular, tend
to learn to use computers and the Internet through play almost without direct
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114 Bernardo Sorj
orientation. However the probability of having the type of access that allows
this kind of learning by osmosis, either at home or work, is lower in low-income
sectors where the chances of owning a home computer or having access to a
computer in the work place are extremely low.
The increasing complexity associated with the fight against social
inequality creates new challenges for strategic planning of governmental
actions and for the development of social policies in which sociological
sensibility can be extremely useful. The urgency to resolve the problem of
the digital divide cannot justify hasty pharaonic investments in areas that
demand experimental pilot programs, adequate local conditions, user
training, systems of evaluation and technical support. This is particularly
true of the installation of Internet access in schools, which should be
distinct from viewing the school as place in which deprived children can
have access to the Internet as an educational tool. ICTs should not be
transformed overnight into a privileged instrument for the educational
system. The adaptation of professors to this new instrument is a long
process that cannot be disassociated with the general improvement of
professional development. Developing adequate software, adapting
pedagogical systems, and developing critical teaching techniques on the
use of ICTs will be a necessarily long term learning process in the majority
of developing countries. Until that time, the role of ICT labs in schools
should be to introduce students to these instruments and their uses and
provide them training on basic programs, in order to motivate them and
to facilitate future integration in the job market.
Finally, the fight against the digital divide depends, above all, on the
capacity of state action to use market impulses and the experiences of civil
society, non-governmental organizations and private initiatives to assure
that poor sectors of the population are integrated into and participate in
the construction of the global society. For instance, the experience in
several Latin American countries indicates that NGOs or state free public
tele-centers in poor neighborhoods have a pioneer role in opening a niche
which is generally rapidly overtaken by the private initiative of locals that
offer good services with very low tariffs.
Conclusions
The consequences of the Internet on social stratification are a disputed
terrain in the sociological literature. While there are reasonable
arguments for considering the Internet as a tool to diminish social
distance, democratizing knowledge, and social participation, it can be
equally argued that it increases centers of power, state and corporate social
control (e.g., among the “optimist” scholars, see Castells, 2009; Benkler,
2006; or for critical stances, see Grewal, 2008; Zittrain, 2008; Carr, 2010).
Both sides reflect different aspects of social reality and the main criticism
that both perspectives deserve is that the Internet is but one dimension of
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The digital divide in Brazil 115
social dynamics. Thus, the final impact of the Internet will depend in large
measure on a dynamic that is outside of the technological realm; or more
properly, on unintended consequences and the economic, social and
political factors that are shaped also, but not only, by the Internet.
In developing countries, where Internet access is not available to large
portions of the population its initial social impact is to increase social
inequality because it reaches first the wealthiest sectors of the population.
Thus, the fight against the digital divide is not so much a fight to diminish
social inequality in itself as it is an effort to prevent inequality from
increasing because of the advantages that those groups of the population
with more economic resources and education enjoy as a result of exclusive
or better access to telematics. Sociological analysis can be particularly
helpful in understanding the different impact of the Internet on different
social strata and age-groups, the ways it impacts on users and the different
forms of appropriation of the technology.
From a policy perspective the struggle for digital inclusion is a struggle
against time. New information technologies increase existing social
inequalities; therefore policies for digital inclusion are nothing more than
a struggle to re-align the possibilities for access to the job market and life
chances of the poorer groups. But promoting access is only a step. The
true value of information depends on the user’s ability to interpret it. To
be useful, information must be meaningful, must be transformed into
knowledge through a process of socialization and practices that build
analytical capacities. Therefore confronting the digital divide cannot be
separated from confronting the educational divide.
E-social development does not substitute for other kinds of social
development, nor does the fight against the digital divide supplant the set
of measures necessary for facing poverty, social inequality, and one of their
most terrible consequences, urban violence. Policies to universalize access
to the Internet in developing countries will not be successful if they are not
associated with other social policies, in particular those relating to
education. Obviously, this does not mean that we must wait until we are
able to eradicate illiteracy in order to develop digital inclusion policies.
The demands of the economy and the labor market require interrelated
policies that work with different social sectors and different rhythms in
order to universalize the Internet as a public service.
References
Benkler, Y. (2006). The wealth of networks. New Haven, CT, US: Yale University Press.
Brazilian Steering Committee. (2011). Survey on the use of information and
communication technologies in Brazil: ICT Households and ICT Enterprises –
2010. Retrieved July 17, 2012 from http://op.ceptro.br/cgi-bin/indicadorescgibr-2010?pais=brasil&estado=rj&academia=academia&age=mais-de- 60 anos&education=pos-doutorado&purpose=pesquisa-academica.
The Digital Divide_BOOK.indb 115
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116 Bernardo Sorj
Carr, N. (2010). The shallows: What the Internet is doing to our brains. New York:
W.W. Norton.
Castells, M. (2009). Communication power. Oxford, UK: Oxford University Press.
Christensen, C., Johnson, C.W. and Horn, M.B. (2008). Disrupting class: How
disruptive innovation will change the way the world learns. New York: McGraw-Hill.
Grewal, S. (2008). Network power. New Haven, CT, US: Yale University Press.
Schacter, J. (1999). The impact of education technology on student achievement: What the
most current research has to say. Retrieved July 21, 2012 from http://www.eric.
ed.gov/PDFS/ED430537.pdf
Sorj, B. (2005). Information societies and digital divides: An introduction. Milan, Italy:
Polimetrica.
Sorj, B. and Guedes, L.E. (2005). Internet y pobreza. Montevideo, Uruguay: Editora
UNESCO, Ediciones Trilce.
Sorj, B. and Lissovsky, M. (2010). Internet in Brazilian public schools: Policies
beyond politics, IRIE – International Review of Informatics Ethics, 14, 41–63.
Witte, J.C. and Mannon, S.E. (2010). The Internet and social inequalities. New York:
Routledge.
Zittrain, J. (2008). The future of the Internet and how to stop it. New Haven, US: Yale
University Press.
Notes
1 It can be argued that Marxist classical class theory was also dualistic, opposing
the owners of the means of production to workers. However, Marx himself and
the Marxist tradition recognize the existence of other social classes
(lumpenproletariat, petit bourgeoisie, peasantry, etc.).
2 In the future the convergence of technologies will increase the need to process
written information, even to manipulate a cell phone, creating an internal
digital divide among users according to their literacy.
3 For instance, in a study we have done on the use of telematics by Brazilian
public schools teachers we concluded that the older the teacher the more
difficulties they have in adapting to the use of telematics as a teaching tool.
4 The Brazilian national institute for statistics (IBGE) is responsible for
collecting data on the digital divide which is periodically elaborated in detail
by the Brazilian Steering Committee. (See Brazilian Steering Committee,
2011).
5 This division is based on using as the main criteria household facilities,
appliances, and level of education. For statistical reasons groups D and E were
fused.
6 Seventy-five percent of users of LAN-houses declared that they had no Internet
access at home.
7 See, for instance, the studies online provided by Learning Point Associates:
http://www2.learningpt.org/catalog/. For a good summary of evaluations
carried out through 2005 see Critical issue: Using technology to improve student
achievement. http://www.ncrel.org/sdrs/areas/issues/methods/technlgy/te800.
htm (retrieved March 6, 2011). The major studies carried out in the 1990s were
summarized by John Schacter (1999). The impact of education technology on student
achievement: What the most current research has to say. http://www.eric.ed.gov/
PDFS/ED430537.pdf (retrieved March 6, 2011). The argument that new
technologies require a radical change in teaching methods in order to be
effective is proposed by C. Christensen, C.W Johnson. and M.B. Horn (2008).
The Digital Divide_BOOK.indb 116
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The digital divide in Brazil 117
Disrupting class: How disruptive innovation will change the way the world learns. New
York: McGraw-Hill.
8 Years ago we analyzed a publication by the World Bank of successful stories of
tele-centers in developing countries. None of the experiences survived the end
of support given by foreign donors to the “benchmark”.
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7 Digitizing Russia
The uneven pace of progress
toward ICT equality
Inna F. Deviatko
National Research University
Higher School of Economics
This chapter addresses major dimensions of Internet-related inequalities in
contemporary Russia including relevant regional, urban/rural, income,
gender, occupation and age-related predictive variables commonly used in
order to operationalize differences in socioeconomic positions of individuals
and families and, correspondingly, in their access to the Internet. The
analysis is based on multiple data sources – from 2007–2010 Russian Federal
State Statistics Service Household Budget Survey data1 to the Public Opinion
Research Foundation (FOM) Internet Use Survey (2002–2011) and other
opinion and market research agencies’ data on Internet coverage among
different population groups. In addition to examining causes of a gap in
access to the Internet using computers and mobile phones, current policies
aimed at closing the digital divide as well as prospects and possibilities of
convergence between different groups of population in patterns of
information technologies usage will be briefly analyzed.2
Talking about the various dimensions of digital divide in Russia, I will
demonstrate the explanatory relevance and great theoretical promise of a
neo-functionalist approach to future research of stratification in the
digital sphere. As the question “Are there any social classes at all?” arises
all the more insistently in the field of stratification research (Weeden and
Grusky, 2005), an alternative account based on what is sometimes called “a
retooled Durkheimian approach to class analysis” (Grusky and Galescu,
2005, p. 53) originating mostly from The Division of Labor in Society
(Durkheim, 1984 [1893]) and based on tracing the differences between
gemeinschaftlich occupational groupings looks more viable at least when it
goes about explaining micro-level variability in individual attitudes,
lifestyles and behaviors (Grusky and Galescu, 2005) not excluding
Internet-based activities and preferences.
Inequality of possibilities and/or inequality in outcomes:
A preliminary overview
By Internet access equality, we mean the idea of equal opportunities for
people to use Internet-based services and information sources in their
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Digitalizing Russia 119
work, educational activities and during their leisure time. One has to note
immediately that the researcher is generally not expecting to discover
identical patterns of Internet usage including such individual-level
indicators as usage time and location of a principal Internet access device,
Internet navigation skills, exact amount of perused content in native and
foreign languages and so on. Variables describing varying patterns of
Internet use, at least analytically, pertain rather to inequalities in outcomes
than to unequal possibilities and a lot of research should be done before
one is able to single out “pure” effects of the initial inequality of
possibilities on outcomes related to Internet use from relevant effects of
varying individual preferences, abilities, occupation-determined needs
and efforts, life styles and so on. Moreover, the idea of Internet equality
implicitly touches upon the question of whether people have rights to equal
opportunity of Internet access, the positive answer to which could be
reasonably disputed (Cerf, 2012). In order to avoid the outlined conceptual
and analytical difficulties I will discuss differences in Internet access
available to subpopulations and major socio-demographic groups in
Russia mostly in a descriptive way focusing primary attention on the
equality of opportunities and avoiding overtly axiological judgments.
In comparative perspective, Russia currently ranks thirty-sixth on the
Household Download Index from Speedtest.Net 3 which is “comparing and
ranking consumer download speeds around the globe. The value is the
rolling mean throughout in Mbps over the past 30 days where the mean
distance between the client and the server is less than 300 miles” (Net
index by Ookla, 2012).
Other possible comparative estimates include the BCG e-Intensity
Index which comprises different measures of Internet activity across
nations. It is computed as a weighted sum of three sub-indices: 1) enablement
(quality of infrastructure in terms of broadband penetration and
availability of access − 50 percent), 2) expenditure (money spent on online
retail and online advertising – 25 percent), and 3) engagement (extent of
Internet use by businesses, governments and consumers – 25 percent). The
index is calculated by The Boston Consulting Group which recently
published a report on Internet influence upon the Russian economy which
gives a BCG e-Intensity Index value of 52 for Russia which could be
compared to 53 for Brazil, 41 for China and 140 for Denmark, currently
heading the BCG rating (The Boston Consulting Group, 2011, pp. 13–17).
For the third quarter of 2011, the monthly Internet audience in Russia
(the number of people over 18 years old, living in Russia and going online
at least once a month during the analyzed period) reached 44.98 percent
– an estimate based mainly on data from the Public Opinion Research
Foundation (FOM) Internet Use Survey (as cited by Russian Internet
statistics service Russian Domains at: http://statdom.ru/internet#29:
level=2). Internet penetration for Moscow and Saint Petersburg during the
same period supposedly exceeded 69 percent. In June 2011 iKS-Consulting
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120 Inna F. Deviatko
claimed that the penetration of broadband access to Internet in Russia for
households reached 36 percent with 19 million private consumers (iKSConsulting Agency, 2011). The household-level data on growth in
possession of personal computers and PDAs from 2001 to 2009, shown in
Figure 7.1, clearly demonstrate the dramatic increase in technical
opportunities of getting access to the Internet, corroborating the general
conclusion of the recent expansion of the Internet audience in Russia.
The picture of augmentation in Internet use in the last decade can be
supplemented by data on the purposes of Internet use (Table 7.1).
Predictably, purposes of “personal communication and information
exchange in social networks, e-mailing relatives and friends” and
“downloading movies, music, games; playing online games” are gaining a
lead but “reading the news, getting information from electronic libraries,
encyclopedias” is third in popularity among respondents of the Russian
Federation Federal State Statistics Service household budgets survey. The
evident differences in patterns of Internet use between urban and rural
households emphasize the importance of the geographic dimension of
digital inequality and related differences in infrastructural possibilities
and living standards.
Posession of PC or
PDA/smartphones
PC possession
PDA/smartphones
Number of items per 100 households
60
50
40
30
20
10
0
2001 2002 2003 2004 2005 2006 2007 2008 2009
Year
Figure 7.1 Possession of PCs, PDA and computers, 2001–2009
(Based on data from: Russian Federation Federal State Statistics Service. Central Statistical
Data Base. http://www.gks.ru/dbscripts/Cbsd/DBInet.cgi)
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Digitalizing Russia 121
Table 7.1 Patterns of Internet use: Percentage of urban and rural households using
the Internet for different purposes in 2010
Purpose of Internet use (for all households All households
having Internet access in a group):
using the
Internet
(100.0)
Urban
households
(100.0)
Rural
households
(100.0)
9.4
10.5
3.9
Finding information, drawing up
documents, performing paperwork
on and the websites of government
institutions and state agencies
18.8
20.4
10.2
Searching for information on
products and services, buying/
ordering goods, booking services,
putting up personal advertisements
on sale of personal belongings or
real estate
37.7
41.1
19.6
Banking online (making payments,
money transfers, etc.)
12.2
13.9
3.3
Distance learning (compulsory or
optional educational programs)
12.3
12.5
11.0
Reading the news, getting
information from electronic
libraries, encyclopedias, etc.
72.6
74.9
60.7
Personal communication and
information exchange in social
networks, e-mailing relatives and
friends
83.5
84.3
79.4
Discussion of social and political
issues, participation in Internetbased campaigns and public opinion
polls, etc.
10.3
11.6
3.5
Downloading movies, music, games;
playing online games, etc.
78.2
79.1
73.5
9.4
8.4
14.7
Finding a new job or performing
paid work, mailing information
Other purposes
(Source: Household incomes, expenses and consumption in 2010, based on the household
budgets survey of the Russian Federation Federal State Statistics Service.)
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122 Inna F. Deviatko
Geography matters? Regional and urban/rural differences
in ICT access
Being the largest country in the world (with a total area reaching
17,098,242 sq. km) and comprising immense, sparsely populated territories
with uncongenial climates (the average population density being about 8.3
people per km2 as can be seen from the 2011 Federal State Statistics Service
of Russian Federation data). Russia has always been a kind of challenge for
major infrastructural projects. Providing equal possibilities of access to
digital communications to a population dispersed over the vast territories
has proved to be a difficult task (see Figure 7.2).
As data on urban and rural households having access to Internet
(Tables 7.1 and 7.4) show, the differences between the general levels of
Internet usage and specific activities remain strongly pronounced due to
Year
Percentage of households with Internet access
60,00
2005
2006
2007
2008
2009
50.00
40.00
30.00
20.00
10.00
Siberian district
Urals district
Far Eastern district
Federal district
Volga district
Southern district
Saint-Petersburg
Northwestern
Moscow
Central district
Russian Federation
0.00
Figure 7.2 Percentage of households having Internet access by federal districts,
2005–2009
(Based on data from: Russian Federation Federal State Statistics Service, Central Data Base,
household budgets survey indicators, http://www.gks.ru/dbscripts/Cbsd/D)
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Digitalizing Russia 123
the higher costs of providing fixed access for rural households. However,
some recent data from the FOM Internet in Russia: Penetration Dynamics.
Summer 2011 survey (FOM (Public Opinion Foundation), 2011) hint at
the possibility of mobile broadband access superseding the fixed access for
the rural population.4
Table 7.2 demonstrates interregional differences in Internet coverage
roughly reflecting the general population settlement patterns: the Central
Federal District ranking first among major administrative regions (i.e.
federal districts) in population density (57 people per km2) and third in
percentage of households having Internet access; the Southern Federal
District (including the North Caucasian District in 2009) being at the
bottom of the list with rural population predominant in some of the North
Caucasus upland regions (Dagestan, Chechnya, Ingushetia, and KarachayCherkessia).
Yet the influence of income on Internet access cannot be fully isolated
from “purely” geographical factors like population distribution and spatial
allocation of big cities and large industrial areas. Predictably, a perfect
correlation is observed between average per capita monthly incomes and
Internet-access levels for federal districts.5 In a following section the
influence of per capita income on Internet access is examined more
thoroughly.
Table 7.2 Percentage of households having Internet access by federal districts,
2008–2009
2008
2009
Central Federal District i
25.3
31.4
Moscow
48.2
53.0
Northwestern Federal District ii
26.6
39.4
Saint Petersburg
33.2
46.8
Southern Federal District (until 2009)
14.1
19.9
Volga Federal District
18.2
24.6
Urals Federal District
26.2
31.8
Siberian Federal District
17.0
25.9
Far Eastern Federal District
23.1
30.6
i Including Moscow.
ii Including Saint Petersburg.
iiiHBS question: “Do your household members have access to the Internet at home?” (Yes, no).
(Source: Based on data from the Russian Federation Federal State Statistics Service, Central
Data Base, household budgets survey indicators, http://www.gks.ru/dbscripts/Cbsd/
DBInet.cgi)iii
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124 Inna F. Deviatko
Income inequalities and inequalities in Internet access:
A progressive convergence?
As the Russian Federation Federal State Statistics Service data show,
income remains a major influence upon the possibility of using the
Internet (see Table 7.3), but a comparison between rates of households
having Internet access in income deciles for years 2008 and 2010 shows
some tendency for the initial gap to be bridged. Diminishing costs of
getting Internet access have led to a reduction of the difference between
the first and the tenth deciles from 33.1 to 24.5 percentage points. The
2010 data also shed some light on differences in purposes for using the
Internet among income groups. Here we cite only minimal and maximal
percentage values for using the Internet in educational and work-related
purposes:
•
•
•
•
finding a new job or performing paid work – 4.4 percent in the lowest
decile and 15.9 percent in the fourth decile;
finding information, drawing up documents, performing paperwork
on the websites of government institutions and state agencies – 6.9
percent in the lowest decile and 29.8 percent in the ninth decile;
searching for information on products and services, buying/ordering
goods, booking services, putting up personal advertisements for sale
of personal belongings or real estate – 25.5 percent in the sixth decile
and 49.4 percent in the ninth decile;
distance learning – 7.2 percent in the highest decile and 21.2 percent
in the fourth decile.
These data defy a possibility of a straightforward Marxist interpretation of
income inequality as derivative of inequality in possession of the means of
production: Internet use for purposes related to production does not
neatly follow the dividing lines between income groups and vice versa.
Particularly, data on using the Internet for distance learning in lowincome deciles as compared to the highest decile do not give direct
support to the idea of alienation of lower-income groups from their work
and educational prospects. Lower-income groups demonstrate the
tendency to control at least some aspects of their lives and freely develop
their individuality through Internet-based access to educational facilities
without having to wait until the revolution “puts the conditions of free
development and movement of individuals under their control” (Marx and
Engels, 1970, p. 85). However, currently available data do not allow us to
check a more complicated model differentiating between occupation,
income, class and ways of using the Internet for production purposes
(including knowledge production and human capital accrual).
Recent governmental efforts directed at promotion of wider Internet
use for educational and production related purposes (through direct
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3rd
4th
2.6/3.9
0.6/0.2
0.3/1.0
• from a place of
study (school,
etc.)
• from an
Internet-cafe
• other
0.6/1.2
0.7/0.7
3.5/3.4
7.4/8.9
0.8/0.7
0.9/3.1
3.4/3.8
8.9/9.5
16.7/35.8
6th
7th
1.0/0.6
1.1/0.4
4.1/3.5
10.2/14.1
1.3/0.7
0.9/0.3
4.2/3.1
1.0/1.0
1.0/0.4
4.4/3.7
13.5/16.0 17.5/20.0
20.3/37.2 24.6/38.8 34.7/47.2
30.1/44.6 33.5/45.5 44.7/54.1
5th
9th
The highest
decile
1.1/1.2
0.7/0.2
2.7/3.0
0.8/0.8
1.0/0.2
2.0/1.7
1.5/0.9
1.3/0.0
3.3/1.6
21.2/23.5 23.0/25.0 23.9/25.4
38.8/53.3 34.1/50.9 29.8/47.2
49.3/60.8 44.6/59.1 44.4/55.5
8th
(Source: Based on data from the Russian Federation Federal State Statistics Service, the sample survey on households’ budgets
(http://www.gks.ru/free_doc/new_site/population/urov/urov_635.htm and http://www.gks.ru/bgd/regl/b10_102/IssWWW.exe/Stg/god/03-06.htm)
0.7/1.2
1.2/0.7
3.1/3.7
5.9/9.4
3.9/7.7
• from an office
computer
14.6/33.8
18.2/38.9 22.1/40.6 25.6/41.7
11.0/32.2
11.3/31.0
The lowest 2nd
decile
• from a home PC 6.0/25.5
Including:
Percentage of
households having
Internet access (of
all households in a
decile) in
2008/2010
Group
Table 7.3 Internet access by income decile in 2008 and 2010 compared
126 Inna F. Deviatko
communication infrastructure investments and money transfers to
corresponding state and municipal agencies) are epitomized in two major
programs: the Digital Russia Program (2002–2010) and the Digital
Government Program (from 2008 on), which succeeded it. The Russian
Ministry of Information and Communications reported recently (ITARTASS News Agency, 2011) that the United State and Municipal Services
Portal (http://www.gosuslugi.ru/ru/), launched in 2008 under the aegis
of the Digital Government Program, now serves 1.3 million individual
users with an average monthly increase of 100,000 newly registered clients.
Besides this, the federal budget now funds the publicly available Internet
connection program for primary and secondary schools which currently
covers about 90 percent of Russian regions (RIA Novosti News Agency,
2010).
Gender, occupation and age-related differences in
Internet access
Recent data from a TNS Web Index Report (TNS Russia, 2011) shows that
a gender balance in Internet use – 51 percent males and 49 percent females
– is now approaching the general proportion of females and males among
Russian adults, following a period of moderate male predominance among
Internet users (the later fact could be at least partly attributed to moderate
male predominance among younger age groups which are better
represented among Internet users).6 Though, it should be kept in mind
that the Web Index data are gathered and combined from two sources: a
regular offline survey based on telephone interviews with urban dwellers
aged over 12 (from cities with populations over 100,000) and an online
Internet-access panel survey. The nature of the data currently defies the
possibility to evaluate the statistical validity of this and other conclusions
in any direct way (however TNS Russia recently advertised the creation of a
supplementary “user-centric” panel which should make the task easier).
The other source of our data is the Russia Longitudinal Monitoring
Survey (RLMS) which provides, in particular, high-quality individual data
on Internet use. The only serious restriction on comparability of the RLMS
data7 on Internet use stems from the exact wording of questions on
Internet usage, technical devices used for getting access to Internet,
locations and purposes of use: relevant questions define the period of
interest as “the past 12 months” (e.g., Have you used the Internet in the past 12
months?). Nevertheless we can use RLMS data for some comparisons with
regards to the socio-demographic features of Russian Internet users. Most
recent data (RLMS 19th Round, 2011, available at: http://www.hse.ru/
rlms/spss) on gender composition of Internet users give a slightly different
picture: among those 80 percent of adult individuals who have used the
Internet in the previous 12 months, there were 45.5 percent males and
54.5 percent females. Even being mindful of the intricacies of comparing
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Digitalizing Russia 127
heterogeneous data, the existing empirical evidence allows us to detect the
rapid closing (or even possible disappearance) of the gender digital gap in
Russia, which can be compared with similar trends among American
adults (Witte and Mannon, 2010, p. 27). Data on the purposes of Internet
use by gender obtained from the same data source demonstrate few
statistically significant differences at the 0.05 level, in particular, for using
the Internet for entertainment (83.4 percent of males and 74.1 percent of
females who used the Internet answered positively) and work (41 percent
of males and 47 percent of females) – a fact which purportedly reflects
some remaining gender role-specific differences in occupational structure
and leisure time.
The TNS Web Index Report (TNS Russia, 2011) gives some clue as to
the occupational structure of the Internet audience in Russia:
approximately 13 percent were managers, 28 percent were professionals
(including specialists and white-collar workers), 20 percent were students,
17 percent were workers, 8 percent were housewives and 14 percent were
under the unspecified label “others” among Russian Internet users in
November, 2011. RLMS data for 2011 provide a more detailed, though
somewhat discrepant, picture of shares of major occupational groups
4,3
5,7
20,4
28,9
Occupational group
Managers
Professionals
Technicians
Clerical workers
Service and sales
workers
Skilled agricultural
workers
Craft and related
trades workers,
operators
Unskilled occupations
0,2
11,3
5,9
23,4
Figure 7.3 Major occupational groups in yearly Internet audience (% of all
respondents who used Internet during the past 12 months) (Based on:
RLMS, 2011)
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128 Inna F. Deviatko
among the general yearly Internet audience in Russia, as shown in Figure
7.3. Professionals and technicians account for 28.9 percent and 23.4
percent respectively among Internet users8 which harmonizes well with a
functionalist vision of Internet use intensity in professions based on
expert knowledge but skilled industrial, construction and technical
workers and machine operators now also form a considerable share of
the Internet audience.9
Different age groups are represented unequally among Russian
Internet users. Younger groups (especially those between 16 and 35) are
much more active in using the Internet and, generally, people of
productive age are more active than the elderly (Tables 7.4 and 7.5). This
gap is narrowing rather slowly following a path similar to the one
observed among American adults (Witte and Mannon, 2010, pp. 28–29)
though recent data from FOM Internet penetration research reveals a 10
percent share of Internet users for Russian adults aged over 55 (FOM
(Public Opinion Foundation), 2011) which doubles the 2009 estimates
(Table 7.4).
General discussion and some conclusions
It is now slightly more than a decade since P. DiMaggio and E. Hargittai
called for “an expanded paradigm” to describe new digital inequalities
typical for the epoch of rising Internet penetration level (DiMaggio and
Hargittai, 2001, p. 4). But perplexing methodological problems
immediately arise when one is trying to expand the list of variables
predicting the subtleties of individual patterns and benefits of use by
simply adding indicators for inequalities of outcomes which describe
individual-level Internet-related activities (like inequality of skills or
purposes (DiMaggio and Hargittai, 2001, p. 8)) without specifying ab
origin major dimensions of unequal initial opportunities like class or
occupational structure. This strategy is potentially overburdened with
explanatory circularity and often faces restrictions imposed by the
nature of data available, thus limiting the ability to disentangle complex
effects of “true” inequalities (like intergenerational class effects) from
effects caused by preferences, previous training and experience, etc.
Unfortunately, the current state of the basic sociological concepts of
class and status (when even an analytical review of recent research on
inequality prefers to describe the latter in a non-antagonistic language
of observed economic disparities (Neckerman and Torche, 2007)) makes
the task of revealing the most basic dimensions of “true” inequality
rather formidable.10 It becomes even more formidable in the effort of
interpreting consequences for stratification systems and attendant new
inequalities (or even equalities) in education, work and leisure of those
rapid and massive social and economic transformations which have been
taking place in post-Soviet societies since the late 1980s.
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Digitalizing Russia 129
Table 7.4 A ge-related differences in regular Internet access for rural and urban
households (percentage of the total number of household members in a
relevant age group, for age groups under 74)
All Households
Households:
Urban
Rural
2008
2009
2008
2009
2008
16.0
22.6
19.9
27.5
5.1
9.6
Under 16
10.2
16.0
12.7
18.7
4.4
9.4
16 − 35
28.7
38.2
35.2
45.5
8.8
16.8
36 − 55
13.2
20.5
16.6
25.6
4.3
7.5
56 − 74
2.4
4.2
3.0
5.5
0.7
0.5
Regular users ratio for household
members under 74
2009
Regular users ratio for household
members by age groups:
(Source: Households incomes, expenses and consumption in 2009, based on the household
budgets sample survey of the Russian Federation Federal State Statistics Service.)
Table 7.5 Age-related differences in occasional Internet access for rural and urban
households (percentage of the total number of household members in a
relevant age group, for age groups under 74)
All Households
Households:
Urban
Rural
2008
2009
2008
2009
2008
2009
5.6
6.2
6.6
7.2
2.9
3.5
Under 16
2.9
3.2
3.3
3.8
1.9
1.6
16 − 35
6.8
6.1
7.3
6.5
5.1
4.9
36 − 55
7.5
9.4
9.3
11.3
2.7
4.3
56 − 74
1.9
2.7
2.4
3.3
0.5
1.0
Occasional users ratio for household
members under 74
Occasional users ratio for household
members by age groups:
(Source: Households incomes, expenses and consumption in 2009, based on the household
budgets sample survey of the Russian Federation Federal State Statistics Service)
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130 Inna F. Deviatko
The validity of generalizations one may find in authoritative sources on
digital inequalities − e.g., “In today’s information-based economy, Internet
access and use can be understood as an asset used to maintain class
privilege and power” (Witte and Mannon, 2010, p. 81) − is to a considerable
degree threatened by social scientists’ inability to define “big classes”
otherwise than through differences in income, wealth and, to a degree,
education, all of which could be treated as effect-indicators of class
affiliation in any cogent interpretation of a Marxist imagination of class,
defining classes strictly in terms of their relationship to the means of
economic production (not just wealth or “assets” treated too loosely by
some New Left theorists who forget that what can count as an asset
depends on what kind of person is granted this asset).
Available data on gender, occupation and income related differences in
Internet use among Russian adults do not provide decisive evidential
support to theoretical visions of Internet inequalities inspired either by
Marx or by Weber. The basic conclusion of a prevailing importance of
household income in predicting inequalities in rates of access to the
Internet is compatible with both accounts, although it was demonstrated
that data on using the Internet for purposes related to production does
not follow neatly the division lines between income groups − a fact which
could be considered as undermining the possibility of the straight-line
Marxist interpretation. However, whatever the deepest reasons for income
disparities are, the data obtained show some tendency for convergence in
rates of access for different income groups which could be attributed both
to recent trends in diminishing income inequalities among Russian
households and to diminishing costs for Internet access due to the
concerted yet unintentional action of recent technological changes and
market forces. The geographic dimension of inequality turned out to be
equally important with the effects of technological constraints, economic
underdevelopment, population distribution and regional average incomes
resisting disentanglement in the survey data currently available.
The revealed influence of occupational structure on Internet inequality
gives some distinct (but not yet definitive and consistent) evidence
supporting the leading positions of professionals and white-collar workers
among Russian adult Internet users. This conclusion may give a second
breath to the least articulated and underestimated version of stratification
theorizing in sociology dating back to Durkheim and promoted in
Parsons’ writing on modern professions and occupational groupings
(Parsons, 1940; 1971). As already noted at the beginning of this chapter a
kind of neo-Durkheimian approach to analysis of gemeinschaftlich “microclasses” (Grusky and Galescu, 2005) could be helpful for explaining
sources of observed differences in the occupational structure of the
Internet audience in Russia. Our data on differences in Internet use
intensity between professionals, technicians and the rest can be accounted
for by work-based distinctions stemming, in the final analysis, from the
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Digitalizing Russia 131
technical division of labor and coming into being at the disaggregate level
through the processes of occupational self-selection, repeated social
interactions among co-workers, explicit professional training and
socialization, etc. (Grusky and Galescu, 2005).
It goes without saying that more substantive evidence in support of all
these preliminary conclusions depends on both elucidation of our
theoretical formulations of deeper causes of inequality and
methodological progress in empirical research on qualitative and
quantitative disparities in Internet access in Russia.
References
Cerf, V. (2012, January 4). Internet access is not a human right. The New York Times,
p. A25.
DiMaggio, P. and Hargittai, E. (2001, Summer). From the ‘digital divide’ to ‘digital
inequality’. Princeton University Center for Arts and Cultural Policy Studies Working
Paper Series (#15).
Durkheim, E. (1984 [1893]). The division of labor in society. New York: The Free Press.
Federal State Statistics Service of Russian Federation. (2011). The modern
demographic situation in Russia: An analytical report. Retrieved from http://www.
gks.ru/wps/wcm/connect/rosstat/rosstatsite/main/population/demography/.
FOM (Public Opinion Foundation). (2011). Internet in Russia: Peneration dynamics.
Moscow. Retrieved from http://corp.fom.ru/projects/23.html#1.
Grusky, D. and Galescu, G. (2005). Foundations of a neo-Durkheimian class
analysis. In E.O. Wright (Ed.), Approaches to class analysis (pp. 51–81).
Cambridge, UK: Cambridge University Press.
iKS-Consulting Agency. (2011, July 6). The Big Four consolidate the market (in
Russian: «Большая четверка» консолидирует рынок). Retrieved from http://
www.iks-consulting.ru/topics/thematic/wideband_access/3844317.html.
ITAR-TASS News Agency. (2011, December 20). News of Ministry of Information and
Communications.
Marx, K. and Engels, F. (1970). The German ideology. C. Arthur, (Ed.) New York:
International Publishers, Co.
Neckerman, K. M. and Torche, F. (2007). Inequality: Causes and consequences.
Annu. Rev. Sociol., 33, 335–57.
Net index by Ookla, 2012. Retrieved 8 january, 2012 from http://www.netindex.
com/download
Nisbet, R. A. (1967). The sociological tradition. London: Heinemann.
Parsons, T. (1940, May). An analytical approach to the theory of social
stratifications. The American Journal of Sociology, XLV(6), 841–862.
Parsons, T. (1971). The system of modern societies. Englewood Cliffs, New Jersey, US:
Prentice-Hall.
RIA Novosti News Agency. (2010, May 31). President Medvedev demands Internet
access for 100% of Russian schools. RIA Novosti.
Rosstat (Russian Federal State Statistics Service). (2010). The Demographic Yearbook
of Russia. Moscow: Rosstat.
The Boston Consulting Group. (2011). Russia online: How Internet is transforming the
Russian economy. Moscow: The Boston Consulting Group, Inc.
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132 Inna F. Deviatko
TNS Russia. (2011). TNS Web Index Report. Moscow. Retrieved from http://www.tnsglobal.ru/rus/data/ratings/index/.
Weeden, K. A. and Grusky, D. (2005). Are there any big classes at all? In D. Bills
(ed.), The shape of social inequality: Stratification and ethnicity in comparative
perspective (Vol. 22. Research in Social Stratification and Mibility, pp. 3–56).
Amsterdam: Elsevier.
Witte, J. C. and Mannon, S. E. (2010). The Internet and social inequalities. New York
and London: Routledge.
Notes
1 The sample survey on households’ budgets has been conducted in all regions of
the Russian Federation since 1997 and covers 47.8 thousand households. The
returns of the survey are compiled quarterly and for a year as a whole.
2 It should be stated in advance that different Internet-related data sources used
in this chapter are sometimes not in complete agreement with each other and
in some cases look inconsistent even within themselves (for example, even a
cursory glance at data on households’ access to the Internet by federal districts
in Figure 7.2 based on our most reliable statistical source – Russian Federation
State Statistics Service databases – discovers enigmatic yet order-preserving
slumps in 2007 and 2008 access rates which can be attributed both to possible
methodological changes in exact question wordings and changing definitions
of Internet-access regularity). The reasons for these and other discrepancies
vary widely and cannot always be easily pinpointed to a specific source like a
lack of commonly used methodological conventions in the field of
conceptualization and measurement of variables related to digital
communications and public and private usage of information technologies.
Although detailed discussion of existing threats to reliability and validity of
ICT-equality related data lies beyond the scope of this chapter, special attention
to any variations and differences in data collection techniques and available
estimates will be paid whenever multiple data sources are used.
3 The current value of the Household Download Index for Russia (11.61 Mbps) is
calculated for data obtained between December 8, 2011 and January 6, 2012
http(http://www.netindex.com/download/, access date – January 8, 2012).
4 Numerical estimates based on this FOM survey should be treated with caution and
compared to other data sources. Consider, for example, the following overblown
estimate that 31 percent of the rural population aged over 18 has mobile access
(e.g., http://raec.ru/upload/files/pages-from-in-numbers8_1.pdf).
5 Pearson’s r=0,995 for 2008 year data, p < 0.01 (and r=0.812 for 2009 year data is
also significant at the 0.01 level).
6 The Demographic Yearbook of Russia, 2010 (Rosstat (Russian Federal State
Statistics Service), 2010) gives 45.3 percent (53928245) for males and 54.7
percent (65131870) for females aged over 16 in the general population (as
could be calculated from Table 1.10 data) with female predominance only for
age groups over 55 and male predominance in younger age groups.
7 Source: Russia Longitudinal Monitoring Survey, RLMS-HSE, conducted by the
National Research University Higher School of Economics and ZAO
“Demoscope” together with Carolina Population Center, University of North
Carolina at Chapel Hill, and the Institute of Sociology RAS.
8 p < 0.01.
9 Among those RLMS 19th Round respondents who were currently employed
(N=7792), 4.4 percent were managers, 19.2 percent were professionals, 17.9
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Digitalizing Russia 133
percent were technicians, 5.4 percent were clerks, 13.1 percent were service and
sales workers, 0.4 percent were skilled agricultural and fishery workers, 28
percent were craft and related trades workers and machine operators, and 11.7
percent were unskilled workers.
10The shrewd comment formulated by R. Nisbet in the late 1960s remains
relevant for the significant part of sociological research in the field of
stratification and inequality: “Only after the historic and essential bases of
social class in European society had become tenuous and uncertain, had
become threatened by forces such as political centralization, citizenship and
mass education – forces which would, in the long run, make class the weakest of
all traditional social unities under the modern regime – did the study of social
stratification burst forth in full brilliance” (Nisbet, 1967, p. 174).
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8 The digital divide in India
Inferences from the information
and communication technology
workforce
P. Vigneswara Ilavarasan
Indian Institute of Technology Delhi
The present chapter examines the digital divide in India using the case of
the workforce in the information and communication technology (ICT)
industry. It studies the digital divide in access and use of the Internet using
a social inequality lens. Social inequality can be explained in multiple
ways. The conflict perspective, which originated from Karl Marx, argues
that the society is in a continuous friction between two groups over
resources. The dominant group in terms of ownership of resources will
tend to suppress the other group in order to maintain the status quo over
the resources through all possible ways. The institutions in the society will
be manipulated to maintain the dominance in a perpetual manner thus
resulting in overall social inequality. The other suppressed group explores
breaking this dominance with consequent reactions resulting in conflicts.
The conflict will be constant, but the nature and form of resources will
change. The resources rooted in economic capital can also morph into
other forms of capital, like cultural or social (Bourdieu, 1986).
According to the conflict perspective, the ownership of and access to
the Internet will also be part of the resources. The dominant class or
group will have better ownership of and access to the Internet than the
others. The paths to acquire the resources, computer ownership, expertise
to use the Internet and the forms of content of the Internet, for example
English language, will be controlled by the dominant class to block the
entry of the other classes.
The cultural perspective has its origins in the works of Max Weber and
deviates from the conflict perspective by bringing forth the importance of
“status” in explaining social inequality. The status denotes a distinct set of
lifestyles and world views. The individuals come together through a
collective understanding of and adherence to lifestyles to form status
groups or define status positions. The family background and
occupational group are two important factors in deciding ones’ status
position (Witte and Mannon, 2010). Though there is a possibility of better
economic positions conferring higher statuses, not all trajectories are
linear. In other words, not all high paying jobs result in higher prestige.
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The digital divide in India 135
The cultural perspective approaches the Internet as a part of the lifestyle
or distinct culture of a restricted group used to differentiate it from others.
Unlike in the US, data on access and use of the Internet across various
social groups are unavailable in India for social science research. The
extant data on Internet use from the private agencies offers little insights
on how various social groups are faring in the digital space. Given these
limitations, an occupational group, the workforce in the ICT industry, is
examined to understand the digital divide in India. This examination is
carried out within the frameworks of two sociological perspectives:
cultural and conflict.
This chapter is in five sections. The first section discusses the available
statistics on ICTs in India. The second section links the idea of the digital
divide and the ICT workforce in the light of sociological discourse. The
third section discusses the presence of the digital divide in the ICT
workforce. The fourth section seeks to explain the exclusion process that
resulted in the digital divide. The fifth section concludes the chapter.
India and ICTs
India is comprised of 28 states and 7 territories and is the largest
democracy in the world with 1.2 billion people. It is one of the fastest
growing economies in the world and has been adopting liberalization
policies since the early 1990s. Despite the fact that the Indian ICT industry
is one of the favored destinations for software and business process
outsourcing in the world, the ICT infrastructure in India is relatively
unimpressive. In a measurement of electronic government by the United
Nations (UN, 2010) using an index of three components (online service,
telecom infrastructure, and human capital), India was ranked 119 out of
183 countries in the world, inferring weak ICT infrastructure in the
country. Out of a wide range of ICTs, mobile phones are predominantly
used, but high value functions like mobile Internet penetration or 3G
services are still in nascent stages.
In 2011, there were around 771 million wireless phone subscribers.
Mobile tele-density is 65 percent for the country with relatively poor teledensity in rural locations (31 percent) when compared to urban locations
(143 percent). Internet penetration is low with only 11.21 million
broadband subscribers as of 31 Jan 2011 (GoI, 2011). A private research
study estimated that mobile Internet usage was 2 million in 2009 (IAMAI,
2009). Rough estimates (IAMAI, 2011) show that the number of cybercafés
in India exceeds 10, 000, with these most likely to be located in urban
locations. Twenty-four percent of the households use the Internet. These
details suggest the urban bias in ICT access in the country.
The extant large scale data on ICTs in India does not permit
disaggregated analysis with respect to any social groups and the Internet.
The Indian government recognizes the lacuna in the statistical framework
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136 P. Vigneswara Ilavarasan
and is making efforts to include ICT indicators (OECD, 2007). Given the
low penetration of the Internet, there is a possibility that access to the
Internet is present only among the privileged groups. Maplecroft (2011)
warns that the digital divide in India is severe when compared to other
BRIC countries and “most [people] cannot afford ICTs (only 3 percent of
households own PCs), lack the education required to use it effectively
(India has secondary school enrolment rates of 55 percent and adult
literacy rates of just under 63 percent) and are located in geographical
areas that have little or no connectivity to ICT services” (Maplecroft.com,
2011, para. 6).
State-level data (GoI, 2012) show that out of 19.7 million Internet
subscribers as of December 2011, 19.6 percent are located in Maharashtra,
11 percent are in Tamil Nadu, 9.8 percent are in Delhi, and 8.6 percent are
in Karnataka clearly indicating the dominance of developed states in
accessing the Internet.
The Indian government is making significant efforts to enhance the
overall ICT infrastructure through the National E-governance Plan (for
details see DIT, 2011). As a part of this plan, Common Service Centers
(CSCs), a variant of the tele-center model, are being established across the
country (for details see, http://www.csc-india.org). One CSC in each eight
villages will connect all citizens to all public and private services, including
the Internet. If this is successful, all citizens will have access to the Internet
through the more than 100,000 planned CSCs, thus bridging the digital
divide. Currently, there are no studies that directly examine the usage of
CSCs by disadvantaged groups. However, studies on tele-centers in the preCSC period show that social inequalities are reflected in these initiatives.
The digital divide in India
The social stratification in India is predominantly caste based. The
constitution of India classifies the citizens into four categories: scheduled
castes (SCs), scheduled tribes (STs), other backward classes (OBCs) and
the open category (OC). SCs are depressed classes, and were untouchables
in the traditional India. STs are the indigenous people. OBCs are people
who have lower social, economic and educational statuses, but better
statuses than those of the SCs and STs. The OC includes the rest of the
people. This categorization implies that the OC members are from an
upper caste/upper class, and have relatively better educational positions in
society. Similarly, persons belong to SC/ST categories come from a lower
caste/lower class, typically have poor educational backgrounds, and are
considered as the disadvantaged groups in India.
The classification of people forms the basis for most of the policy
measures in the country. As per the 2001 Census, the literacy rate of SCs
and STs was 54.7 percent and 47 percent, respectively, compared to the
national level of 64.8 percent. In the public employment and education
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The digital divide in India 137
systems 15 percent, 7.5 percent and 27 percent are reserved for SCs, STs
and OBCs, respectively. Despite the reservations, SC/STs and OBCs are
underrepresented in the areas of education and employment, with SCs
and STs lagging notably behind OBCs (for details see Deshpande, 2006;
Mohanty, 2006). This chapter will make an attempt to capture the presence
of SC/STs in the digital space in India.
In a study of 132 tele-centers in South India (Kumar and Best, 2006), it
was found that usage by SC/STs is relatively lower and locating tele-centers
in SC/STs neighborhoods appears to be an important factor in increasing
the usage. Their study also pointed out that Internet usage is significantly
related to higher literacy, economic status, and youth. Another study on use
(Thomas, 2006) found similar trends and reinforced the point that “people’s
capabilities to use ICTs are associated with the existing level of socioeconomic development” (p.130). These findings suggested that policy
initiatives might result only in “theoretical access” and not in the “effective
access” by which the individual feels able to access (Selwyn, 2004).
The poor or limited access or use of ICTs by SC/STs can be explained
through two theoretical perspectives: conflict and cultural. Similar
approaches were used by Witte and Mannon (2010) to explain the
inequalities in access and use of the Internet in the US Through a review
of conflict theories, the authors argue that unequal access to ICTs,
especially the Internet, by disadvantaged groups is the result of lower class
background conferred by lower parental education, employment status,
and family income. This uneven access and use between the ruling (and
elite) classes and the ruled (or working) strata will reproduce the class
positions of the respective parties, thus maintaining the ongoing social
inequality. The ruling capitalists sustain their dominance by keeping the
class assets as an advantage in the production process. The class assets
include skills to access and use ICTs.
A cultural perspective adds cultural factors to the economic status to
explain the inequalities. The elite reinforces its dominant status and the
inequalities by its lifestyle and consumption patterns which include
things like “membership of the right club, living in the right
neighborhood, and being invited to the right parties” (Witte and
Mannon, 2010, p.86). The nature of occupations and families are
important in determining the nature of access and use of ICTs which in
turn determine or maintain the prestige status of the dominant class.
The dominant class will be homogeneously situated in positions that
access the resources including ICTs. Witte and Mannon (2010) showed
that people with better educational and occupational prestige, typically
in managerial/professional occupations, perform high-skilled Internet
activities, product searching, or online banking and are most likely to
use the Internet at work, as compared to low-skilled Internet activities
such as emailing or reading blogs, typical of the lower educational and
occupational categories.
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138 P. Vigneswara Ilavarasan
Given this, in simple words, SC/STs are less likely use CSCs, as they did
not have access to ICTs earlier and their children study in schools where
there is limited or no access to ICTs. Also, as most of the SC/STs are either
landless laborers or hold low level public office positions (Mohanty, 2006),
even when they use CSCs, the nature of their activities are most likely to be
low-skilled like seeking entitlements such as caste certificates or
certifications of poverty status, rather than other high value added
services.
This chapter examines the digital divide in India by studying one
aspect, SC/STs in the ICT workforce. This is a slight deviation from the
existing literature on the digital divide that tends to focus predominantly
on access and use of ICTs by the individuals or groups. Earlier, DiMaggio et
al. (2001) indicated that “few sociologists have examined the Internet’s
institutional structure, industrial organization, or political economy”
(p.329). A study of representations of disadvantaged or minority groups in
ICT occupations makes an appropriate site for understanding the digital
divide for four reasons. First, on the theoretical level, occupational groups
are status groups where use of ICTs is part of lifestyle and might be
erecting barriers to the entry of minority groups to maintain the class
privileges. An understanding of the composition of the occupational
group provides insights into the manifestation of the digital divide. Also,
Sassen (2002) argues that digital technologies cannot be studied in
isolation and the “digital space is embedded in the larger societal, cultural,
subjective, economic, imaginary structurations of lived experience and the
systems within which we exist and operate” (pp. 368–369). Second, there is
a paucity of large scale data on access and use of ICTs by citizens (OECD,
2007), thus preventing any disaggregated analysis with respect to SC/STs.
For instance, IAMAI (2011) has collected data from 19,000 households,
68,000 individuals, 1000 Small and Medium Enterprises, and 500
cybercafés, but does not provide any data on the social categories. Third,
ICT occupations directly use, and sometimes produce, the Internet at work
thus making them the frontrunners in cyberspace. The attempts to
measure “ICT for development” by the international agencies use the size
of the ICT workforce as one of the core ICT indicators (see for instance,
ITU, 2010). The non-representation of SC/STs will support the case for the
digital divide. Fourth, the ICT industry in India is treated “as the most
consistent growth driver for the economy” (MIT, 2011) and public policy
initiatives aggressively support the industry. It is also important to
understand whether this sector is digitally inclusive.
The Indian ICT industry is one of the growing parts of the Indian
economy, having grown from US$ 21.6 billion in 2004 to US$ 73.1 billion
in 2010 (NASSCOM, 2011). It contributes 6.1 percent to the GDP and was
estimated to be employing 2.3 million people directly and 8.2 million
indirectly in 2010. The industry is predominantly an exporter of IT and
business process services, which together account for 69 percent of the
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The digital divide in India 139
total revenue in the industry. A trade press report aptly summarized the
status of ICT workers in India:
[the ICT sector] started emerging as a role model for the country. IT
professionals in India were one of the highest paid, on average, IT was
the most sought after area at campus recruitments…IT had the highest
number of people to be nominated for civilian honors by the nation. IT
leaders and news hogged the limelight in the media for the right and
sometimes wrong reasons. IT was the biggest employment generator in
the country. It was IT professionals who were travelling the most into
and out of the country. IT captains were bagging global awards in
business excellence. And as a marriage bureau said, “IT grooms and
brides command the highest premium today, after doctors and IAS
[Indian Administrative Services] officers” (Dataquest, 2006, p. 16).
The digital divide and the ICT workforce
Researchers of the Indian ICT industry, especially on labor or workforce
issues, face serious hurdles as disaggregated data on the composition of
the ICT workforce are not available (Ilavarasan, 2008). The industry itself
is not open for independent researchers as the ICT companies are bound
by the non-disclosure agreements signed with their respective clients.
Given this limitation, this chapter is dependent on the author’s prior
studies and other published studies/secondary data.
Existing small scale survey based studies repeatedly report that
participation of SC/STs is either low or absent. In Ilavarasan’s (2007) study
of 114 ICT workers, there were no SC/STs. This sample corresponded with
the industry average on education, gender, years of experience and
average age of the workforce. Oommen and Sundararajan (2005) also did
not find a single SC/ST worker in their sample of 100, and out of 132
people surveyed there was only one SC/ST in Upadhya and Vasavi’s study
(2006). Though all these studies had modest samples, the findings are
similar. The next social category, OBCs are entering the ICT sector, but in
much lower numbers than their representation in the population as a
whole would suggest, ranging from ten percent (Ilavarasan, 2007) to 20
percent (Oommen and Sundararajan, 2005).
In addition to non-participation of SC/STs, there are other similar
characteristics emerging from the review of existing studies. Regarding
parental educational levels, Upadhya and Vasavi (2006) reported that
“80 percent of respondents’ fathers were graduates or above, and only
three respondents had fathers with less than SSLC [Grade ten] level
education” (p.37).
In Oommen and Sundararajan’s (2005) survey there was only one
father without a school diploma, while Krishna and Brihmadesam’s (2006)
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140 P. Vigneswara Ilavarasan
study had 82 percent of the fathers having a bachelor’s degree or more, but
none had education levels below high school. Accordingly, the
occupational status of fathers followed a similar pattern: most of them
were either in middle or higher public services, professionals, or
businessmen. None of the studies reported a father being a landless
laborer or in an occupation from a lower socio-economic category.
All the studies uniformly found that there was a predominance of urban
backgrounds among the ICT workers. In Ilavarasan’s (2007) study, only 18
percent said that they were from rural places. Similarly, only 12 percent of
respondents came from rural locations in Oommen and Sundararajan’s
(2005) study and slightly more in Krishna and Brihmadesam’s (2006)
study. It was reported as only 5 percent in an ethnographic study (Upadhya
and Vasavi, 2006).
The studies also showed that Hinduism was the dominant religion
among the ICT workers in India. Hindus formed 88 percent in Upadhya
and Vasavi’s (2006) sample. It was 95 percent in Ilavarasan’s (2007) study
and 74 percent in Oommen and Sundararajan’s (2005) survey. Earlier
research showed that Muslims, who form 13.4 percent of the population,
can be compared on a par with the SC/ST in terms of participation in
education and employment (Basant, 2007). Thus, the nature of the ICT
workforce can be summarized as follows: a “typical software worker in
India ...hails from an urban and a semi-urban locality; follows Hinduism,
and belongs to upper socio-economic strata of the Indian society”
(Ilavarasan, 2007, p. 818).
Though the existing studies did not have a detailed presentation of the
caste breakdown of the samples, they indicated the dominance of
Brahmins, a caste of priests and teachers that traditionally occupies the
higher order of social stratification in India. Fuller and Narasimhan
(2008) reasoned that Brahmins would be dominant in the Chennai ICT
cluster as they were among those who were the first to receive Western
education before migrating to urban locations. Earlier, Saxenian (2002)
cited return migration of Indians to start new IT ventures in India as one
of the reasons for the birth and growth of the Indian ICT industry. Taeube
(2004) analyzed the names of the interviewees of all major studies and
argued that “the majority of the key people in the Indian software industry
are located in South India, are Brahmins, and come from a South Indian
background in terms of ethnicity or family affiliation” (p. 219).
The process of exclusion
This section will explain the process by which SC/STs are thwarted from
entering the ICT workforce. The first part of this exclusion process is the
need for an undergraduate degree in engineering or a master’s degree in
sciences. The abundant availability of engineers during the nascent stages
of the sector, the introduction of programs like master’s degrees in
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The digital divide in India 141
computer application and efforts to meet the American visa requirements
for onsite work have resulted in this pattern (Sharma, 2009). There is
direct linkage between the basic training imparted via a college education
and the skill sets required for ICT jobs. In India, the majority of the ICT
workers have engineering degrees in all possible disciplines, which include
textiles, mining and civil, but not necessarily in computer science, software
engineering, or ICT. Unlike their Western counterparts, college dropouts
would not be able to find a job in the ICT industry in India due to specific
hiring practices. The samples of the existing studies clearly support this
observation. For instance, Oommen and Sundararajan (2005) and
Ilavarasan (2007) do not show a single worker with only high school
qualifications or bachelor’s degrees in arts and humanities disciplines.
The supply of SC/STs graduate engineers seems to be lagging when
compared to the other groups. For instance, the urban SC/STs, who are
more likely to be educated than their rural counterparts, have a lower
number of engineering graduates (3.4 percent), when compared to their
share in the total population, (14.5 percent in 1999–2000). These figures
are strikingly lower than the urban Hindu upper castes that comprise 36.9
percent of the population but form 66.8 percent of the engineers
(Deshpande, 2006). High school completion, a necessary condition to
enter colleges, is low among SC/STs. Hasan and Mehta (2006) reinforced
the point that SC/STs are underrepresented in college education. They
showed that among urban males aged 17 to 30, only 7.89 percent of SCs
and 2.69 percent of STs completed a high school education. As the high
school graduation rate is low for these groups, the presence of SC/STs in
engineering colleges is limited. The enrollment of SC/STs in disciplines
that are directly related to the ICT sector and in the national elite
institutions of science and technology are “at best negligible” (Rao, 2006,
p.220). A study (Varma and Kapur, 2010) of undergraduate engineering
students at Indian Institutes of Technology (IITs), one of the top global
schools for engineering education, showed that the “IITs have been
catering to predominantly Hindu students from upper and middle castes
and classes” (p.715). The aspiring students of IITs take private coaching or
tutoring classes to clear the entrance examination which are not
affordable to poor students. The cost of tutoring is around INR 100000
(US$ 2000) per annum which is high for a country where more than half
the population is living on below US$2 per day.
A second filter in the exclusion process is the entrance exam conducted
by ICT firms. The firms hire people directly either at college premises or
at private venues. A fresh entrant needs to have a minimum of 70 percent
grades in high school, higher secondary, and bachelor’s degree education
to appear for an entrance exam (Ilavarasan, 2007; Upadhya and Vasavi,
2006). This criterion is strictly enforced for the entry-level positions to
reduce the number of people to be called for the next round of
recruitment process. The sample of Oommen and Sundararajan (2005)
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142 P. Vigneswara Ilavarasan
showed only one worker with 60 to 70 percent marks. An SC/ST student
who has secured admission to the engineering college due to reservation
policies, but who performs below 70 percent during schooling will be
unable to compete in the open recruitment process.
Third, the personal interviews conducted as part of the recruitment
process serve as a major barrier (Upadhya, 2007). Though some top firms
give one-year jobs directly to the successful candidates based on the
written tests, conducting two rounds of face-to-face interviews, technical
and human resources, is common. Even after assuming that a SC/ST
candidate has scored the required 70 percent in school and college, he or
she is likely to fail in the interviews. As the Indian ICT sector is catering to
the export market, spoken English and good communication skills are
expected. During the interview process, candidates are tested on the traits
of social skills which favor those from more affluent socio-economic
backgrounds who had access to good educational systems (Upadhya and
Vasavi, 2006). An analysis of online advertisements for entry-level ICT
workers showed that social skill traits like personality, teamwork, and
communication skills are identified for possible hiring criteria (Malish
and Ilavarasan, 2011). A recent study shows that SC engineering students
do recognize this shortcoming and start to explore the public jobs where
there is relaxation of marks and no personal interviews (Malish, 2011). Any
attempt to introduce reservation policies in the private sector or the ICT
sector is met with stiff resistance from the industry (see for instance,
Rediff, 2003).
Employee referral programs in ICT firms work as the fourth barrier. It
involves an existing worker referring an external candidate for the vacancy
and getting an incentive on the successful placement of the candidate
(Ghosh and Geetika, 2007). A trade publication reports that the
percentage of people hired through this process ranges from 48 to 60
percent (HR World, 2008; Singh, 2004). This process will also typically
exclude the SC/STs from ICT employment. Given the dominance of nonSC/STs in this sector, the social networks of the current workforce will
prioritize the non-SC/STs. As the workers tend to maximize their
opportunities to earn incentives, the chances of SC/STs entering ICT
employment via referral would be minimal.
Conclusion
The existing discourses on the digital divide focus on the ownership and
consumption of the Internet (Witte and Mannon, 2010). This chapter
analyzed the level of participation of disadvantaged groups, specifically
SC/STs, in the ICT workforce in India, and concludes that the digital
divide prevails.
The exclusion process observed in the ICT industry is a manifestation
of social inequalities and the continuation of class privileges. The
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The digital divide in India 143
strategies used by the elite class to maintain the status quo in this emerging
sector is a combination of forms of cultural capital – educational
qualifications, personality traits, and social networks. These strategies are
not completely driven by the market as the industry is moving from onsite,
where subcontracted work is performed on clients’ sites, to offshore, where
subcontracted work happens in India. Such a recruitment process applies
often to non-engineering graduates as well. Currently, the top ICT firms
are hiring basic science graduates and training them for the international
global production of software (for instance, Chandran, 2011). There is a
possibility of disadvantaged groups entering this sector, but they need to
negotiate the cultural capital barriers.
The ICT sector enjoys a considerable amount of government support in
terms of provision of high-skilled manpower, fiscal incentives, and
infrastructure (Balakrishnan, 2006). Recent government initiatives to
increase the ready-made talent pool available for the ICT sector through
the establishment of 20 more Indian Institutes of Information Technology
(IIITs) with private industry support (Livemint, 2011) or through
permitting private universities to offer programs in ICT-related areas will
increase the existing gap as the cost of education is high when compared
to the public institutes.
The findings from the Indian ICT industry are not different from other
countries. For instance, in the US women and minorities are
underrepresented in computing education and the industry (Simrad,
2009; Varma, 2009). As the production of ICTs are dominated by the
dominant class, the resultant outcomes including the Internet will lack the
creativity brought by diversity and will eventually perpetuate the digital
divide present in the consumption of ICTs. It appears that significant shifts
in thinking are required from both government and industry before
inroads can be made toward bridging the digital divide in the production
space of ICTs.
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9 The digital divide in China,
Hong Kong and Taiwan
The barriers of first order and
second order digital divide
Shu-Fen Tseng
Yuan Ze University
Yu-Ching You
National Taiwan University
Introduction
The International Telecommunication Union (2010) stated that the
global number of Internet users had surpassed 2 billion in 2010, of which
1.2 billion users were in developing countries. The rate of Internet access
has steadily increased from 394 million to over 2 billion in just over a
decade. Despite the significant increase of worldwide Internet users,
global distribution of Internet access has been extremely unequal. While
an estimated 71 percent of the population in developed countries had
access to the Internet at the end of 2010, there was only 21 percent of the
population with access in developing countries. Globally, the Internet
user divide is significantly influenced by gender, age, education, and
income, and there are major differences between urban and rural areas
(ITU, 2011).
This chapter follows Marx’s central theories regarding the economic
relations between capitalists and laborers. Capitalists were defined by their
ownership of the means of production that helped capture surplus value
in the production and consumption processes. Capital was created
through the process of commodities production and exchange. Marx saw
capital as part of the surplus value that creates further profit (Lin, 2001).
In this scheme of the capitalist society, controlling and possessing the
capital, such as tools, technology, and facilities that are associated with
production implies ownership of the resources.
Coming with the diffusion of computers, telecommunications, and
Internet in the 1970s, the information technology revolution
fundamentally restructured capitalism. There has been a shift from
material production to information-processing activities in advanced
capitalist countries. Through infusion and application of information and
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148 Shu-Fen Tseng and Yu-Ching You
communication technologies in the production and consumption,
advanced economies increased their productivity and economy growth.
The new techno-economic system can be adequately characterized as
informationalism (Castells, 2000). The diffusion of information technology
was highly selective. The process and benefits associated with
informationalism were uneven throughout the world. In the information
era, individuals, firms, institutions, regions, and societies are divided into
two groups, those with the material and cultural resources to operate in
the digital world, and those unable to adapt to the speed of change
(Castells, 2001).
Witte and Mannon (2010) provided a useful overview of theories
relevant to understanding inequality in access to and use of the new
information technology. They described how the Internet is a major source
of creating social inequality and social exclusion. Theoretically rooted in
Marx’s point of view, one of their aspects suggested that ownership of
valuable resources, including skill assets, puts certain social classes at a
distinct advantage. Inequality in a capitalist society rests on the ability of a
dominant class to use its assets to maintain an advantage in the productive
process. Individuals with significant Internet competencies and literacy
might enjoy a privileged position in the information society (Witte and
Mannon, 2010).
Since the late 1990s, the unequal distribution of Internet access
between population segments within a society and across nations has
gained recognition among concerned parties, such as scholars, policy
makers, and advocate groups. The development of the Internet has been
suggested as an enabling technology for transforming society, eliminating
power differentials, realizing a free and democratic society, and other
benefits. Lack of access to the Internet or information communication
technology (ICT) jeopardizes one’s opportunity of social participation
and thwarts one’s life chances. Wider uses of ICTs offer considerable
opportunities for those able to take advantage of them, and increased
exclusion for those who cannot. At the national level, poor nations without
high technological investment suffer a competitive disadvantage compared
to their wired rivals in the global economy (Norris, 2001).
Study of the digital divide has focused on the gaps between the
population groups in computer and Internet access and unequal
distribution of Internet services across regional and geographic areas.
Concerning how the national context and political institutions affect
individuals’ technological access and online engagement, Norris (2001)
outlined two contradictory predictions about technological diffusion and
its consequence within a society: normalization and stratification models.
In a normalization model, the differences between groups only increase in
the early stages of adoption. The leading group starts the curve earlier,
along with the resources, skills, and knowledge to take advantage of digital
technologies. In the long run, differences between groups disappear, as
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The digital divide in China, Hong Kong and Taiwan 149
the leading group enters the phase of saturation and the following groups
reveal higher expansion rates, the penetration becomes saturated in these
societies. The optimistic normalization model assumes that Internet
penetration will saturate all groups in society as the Internet becomes user
friendly, less expensive, and its benefits become more widely recognized.
On the other hand, in the stratification model, the higher and lower social
strata start with different resources, while the higher social strata will
reach capacity and start saturation earlier in the curve of adoption. The
pessimistic stratification model assumes that socially disadvantaged
groups will encounter high cost and other obstacles that halt Internet
penetration before they reach the perfect saturation. Norris argued that
the stratification model provides a more realistic scenario where groups
who are already well networked via traditional forms of ICT will maintain
their advantage in the diffusion of new technology. A similar argument
can be found in van Dijk’s (2005) illustration of the “Matthew effect” in
new media access, which indicated that those who already have a head
start in possessing particular resources benefit more from a new resource
than those who are behind and already have some disadvantages.
Much of the research on the digital divide focuses on the first order
effects regarding those who have access to ICTs versus those who do not.
As Internet access gradually increased worldwide during the past decade,
foci on digital inequality studies shifted to the second order digital divide.
While the first order effects focus on the inequality in access to ICT, the
second order addresses the effects of inequality resulting from the
different ways people use ICT technology. Hargittai (2002) argued that as
more people start using the Internet, it becomes less useful to merely look
at the binary classification of whether one is online or not. Instead, she
suggested a need to start looking at the differences in people’s online skill
and stated that how those who are online use the medium is more
important when discussing issues of digital divide.
The second order digital divide stresses a gradual shift of inequality in
the information society from ICT access to ICT usage. The shift to ICT
usage is important because of its implication for social inclusion in that
ICT plays a critical role in all aspects of the new economy and information
society (Warschauer, 2003). Recently, research has shown that the different
usage of ICT can be related to variability in the risk of marginalization,
because differential ICT use can have close interrelations with inclusion or
exclusion in the professional sphere, not to mention access to public
services, consumption patterns, and personal development (Brotcorne et
al., 2010). Scholars argued that unequal attainment of digital skills and the
usage of ICT for particular purposes of information, communication,
transaction, or entertainment is one of the main reasons for the deepening
divide in the information society (van Dijk, 2005). The digital inclusion
study of the UK confirmed that there was a strong association between the
social disadvantages an individual faces and their ability to access and use
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150 Shu-Fen Tseng and Yu-Ching You
digital services. By including users’ online activities in the measurement of
digital exclusion, the UK study discovered individuals with specific
disadvantages appear to be excluded from the applications of technology
that could help them most (Helsper, 2008).
By recognizing the capability of ICT to build various types of capital
through access to relevant Internet resources, we adopt the Marxist
perspective of capital in this chapter. Once individuals have access to ICTs,
and have the capacity to use Internet resources effectively in transforming
them into economic, political and social capitals, they have more freedom
to participate in society in the way they wish to. Those who enjoy the high
levels of economic and social superiority also use their dominant positions
to acquire ICT resources and maintain existing advantages. Individuals
suffering social disadvantages such as low income, less education, and
poorer skills, are more likely to be excluded from the information society.
In this chapter, earlier Internet adopting economies in Asia, such as Hong
Kong and Taiwan, and a fast-growing nation, specifically China, are
compared to test the normalization and stratification hypotheses of
Internet penetration. Secondary and longitudinal data of national ICT
access from the Individual/Household Digital Divide Survey1 in Taiwan
and the Statistical Report on Internet Development in China2 are collected
to examine barriers of the first order digital divides in China, Hong Kong
and Taiwan. A longitudinal comparison across different socio-economic
groups in each of these regions yields results showing whether the
normalization or stratification model better describes Internet
penetration over the past decade. Secondly, activities that people do on
the Internet, such as searching for information, communication,
entertainment, and online consumption, are compared to explore the
divides of digital engagement in these regions. The comparative digital
divides and the social implications of digital inequality in these regions
are discussed in the final section.
The first order divide: Digital access
Early research on the digital divide has focused on inequality in Internet
access. It has generally suggested that Internet access penetrates at varying
rates between different segments of the population (NTIA, 1995). The
gaps generally followed the social inequality lines of gender, age, race,
ethnicity, education and geographic location disparities. Digital
connectivity is essential as lack of Internet access for individuals implies
unequal opportunities for economic mobility and social participation in
the information society. As Internet penetration continues to rise
worldwide, the important question is: does the gap between groups shrink
in the long run as the normalization hypothesis suggested or is the gap is
widening as outlined by the stratification model? The answer to this
question would lead to an optimistic or pessimistic prediction of Internet
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The digital divide in China, Hong Kong and Taiwan 151
diffusion in a society. In this section, trends of the first order divide in
Taiwan, Hong Kong and China are presented (see the figures in Appendix
9.1), followed by a cross-regional comparison of digital access in these
regions.
Trends of digital access
Internet growth has been significant in Taiwan. The annual national
Individual/Household Digital Divide Survey in 2010 illustrated that the
individual Internet penetration rate has exceeded 70 percent in Taiwan.
The household Internet penetration rate also reached 80 percent in
2010. More than half of the Internet users used wireless and mobile
technologies to access the Internet in 2010. The long-term trends
showed that the gap of Internet access between men and women
disappearing in Taiwan. Almost every young adult below the age of 20
used the Internet in 2010. Internet access in the elder groups was
increasing, yet at a slower rate than that of their younger counterparts,
thus resulting in huge gaps when compared to the younger groups.
Those highly educated (college degree or above) were more likely to
access the Internet, and this group showed a saturated Internet
connectivity rate. In comparison, less than 20 percent of people with an
elementary school education or less were connected to the Internet,
thus huge educational gaps persisted. Rural areas generally experienced
lower levels of connectivity when compared to metropolitan areas,
although these gaps appeared to be shrinking. Well-off households have
saturated Internet access and the poor households have gradually
increased their Internet connectivity except for those at the bottom of
the household income range. In broadband connectivity, gaps between
metropolitan city and rural/remote areas were diminishing. However,
those who were better off had broadband adoption rates consistently
higher than those in the vulnerable groups. For mobile Internet access,
steady increases across age and education groups were found,
nevertheless, the gaps among these groups persisted.
Household Internet connection figures have increased significantly
over the last decade in Hong Kong. About 70 percent of households had
access to broadband connectivity. Personal Internet access rates also
increased from 30 percent to 70 percent in the past decade. Consistently,
the rate of having Internet access was slightly higher for males than their
female counterparts. The divides between age groups were shrinking in
general, although there was still a huge gap between the younger group
and those aged 45 and over in 2009. A narrowing trend of Internet access
was found between those who had graduated from senior high school and
those who had college or higher degrees. However, the gap between the
lowest and the highest education groups persisted, with an over 70 percent
discrepancy. The slow increase of Internet access in the lowest income
The Digital Divide_BOOK.indb 151
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152 Shu-Fen Tseng and Yu-Ching You
group led to a huge gap when compared to the highest income group in
Hong Kong.
The China Internet Network Information Center (CNNIC) reported
the number of Chinese Internet users had reached 457 million in 2010 and
the Internet penetration rate was 34.3 percent. Almost all the Internet
users had broadband access. At the end of 2010, China had 303 million
users who used mobile phones to go online, which accounted for 66
percent of total Internet users. There was a slight gender difference in
Internet access in the past few years. The upgrading trend of Internet
access was observed for younger groups; however, the increasing rate of
Internet access was sluggish for the older population groups, thus resulting
in a huge difference compared to the top connected group and a widening
trend of divide between these two groups. Internet access by different
educational levels demonstrated a dramatic increase among those who
had a college degree and a fast catch-up rate of high school graduates in
Internet access. Yet the slow increase in the less educated population led to
a persistent 80 percent gap of Internet access by educational level in the
last few years. Despite the fast increase in the numbers of rural netizens,
the urban/rural digital divide had widened: while 45 percent of the urban
population had Internet access, only 15 percent of the rural population
had used Internet services in 2009.
A cross-regional comparison of the first order divide
Table 9.1 shows the comparison of access divides in Taiwan, Hong Kong and
China. First of all, the table indicates that the gender difference in Internet
access was less significant in these regions. While the gender gap had
disappeared in Taiwan, the proportions of female Internet users in Hong
Kong and China were slightly less than their male counterparts. Age divides
in Internet access in Taiwan and Hong Kong revealed an optimistic
development for those aged under 40, yet the elder groups revealed
persistent gaps when compared to the younger groups. Despite the
impressive increase in numbers of Internet users in China, the age divide of
access had widened, with those aged between 19 and 30 demonstrating a
much higher increased rate of Internet access than the other groups.
Although gradual increases within the less educated groups were found in
Taiwan, the gaps in levels of Internet access across educational groups were
persistent over time. A steady increase in secondary educational groups’
Internet access led to a narrowing gap between this group and the higher
educated group in Hong Kong, however, a huge gap between the higher
educated and the less educated still remained. China revealed the same
trend as Hong Kong did in the decline of the access gap between the
secondary and post-secondary education groups. The secondary education
group in China showed a significant improvement with a shrinking gap
between them and the top group. Yet a persistent divide between the least
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The digital divide in China, Hong Kong and Taiwan 153
educated group and the top one appeared in the past few years. The
regional divide in Internet access in Taiwan demonstrated a similarity to the
normalization model, in that all the remote and rural areas had increased
connectivity and the gaps compared to the metropolitan city had narrowed
over time. By contrast, the access divide had increased along the lines of
geographic location in China, as the Internet access gap between the urban
and rural areas had widened. The income divide in Internet access
resembled the trends of age and education divides both in Taiwan and
Hong Kong, in the manner that the gaps across income groups, except for
those with the least affluent group, were diminishing.
Table 9.1 Summary of the first order divide in Taiwan, Hong Kong and China
Taiwan
Hong Kong
China
Gender
High
penetration
Disappearing
High
penetration
Small gap
persistent
Medium
penetration
Small gap
persistent
Age
Declining yet
Declining yet
Widening
persistent in the persistent in the
older groups
older group
Education
Huge gap
persistent
Declining in
secondary yet
huge gap in the
lowest group
Significantly
declining in the
high school group
yet persistent in
the less educated
group
Region
Declining
—
Widening
Income
Declining yet
Declining yet
—
huge gap
persistent in the
persistent in the lowest group
lowest group
Household
broadband
Region
Disappearing
—
—
Income
—
Narrowing in
the upper
income groups,
persistent in the
lowest income
groups
—
Mobile/
wireless
Gender
Small gap
persistent
—
—
Age
Persistent
—
—
Education
Persistent
—
—
Internet
— Indicates data are unavailable.
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154 Shu-Fen Tseng and Yu-Ching You
The access to broadband services across different geographic regions
in Taiwan showed a more optimistic development in that the regional
gaps in household broadband access were diminishing. The income gaps
in broadband connection were narrowing in the upper income groups,
however, the gap persisted for the worst off group. The divides in mobile
and wireless connection in Taiwan generally showed a declining trend.
The gaps between age groups and educational levels were declining, yet
the gaps still existed.
The second order divide: Digital usage
Recent research has shifted concerns from a simplistic conception of
Internet access to a more complex approach to digital inequality as more
people are using the Internet to communicate, search, entertain, and
engage in online economic and political activities (DiMaggio et al., 2001;
Hargittai, 2002; van Dijk, 2005). A wider range of questions about the
impact of digital access and use on social inequality was raised. In all,
research on the digital divide has moved beyond physical access to pay
closer attention to a multi-faceted concept of access. This second wave of
research on the digital divide was called the “second-level digital divide”
(Hargittai, 2002) or “usage divide” (van Dijk, 2005). By examining the
variation of Internet use, the effects of the digital divide on educational
attainment, earning, social participation and political engagement were
addressed. Scholars focused on the usage gap in the digital divide conduct
research reflecting their concerns of digital inequality across segments of
the population depending on differences among several dimensions of
Internet access and usage. The so called “the rich get richer” or the
Matthew effect implies that in most spheres of societal participation and
political engagement those already occupying the strongest positions tend
to benefit more from access and usage of ICTs as potentially powerful tools
than those occupying the weakest positions (van Dijk, 2005). If the effect
were realized, then those who are already better off would gain more from
the wide ranges of digital technologies used which would lead to a
deepening inequality in society. Information technologies would then
become one more resource for those who already have a large number of
resources to amplify their social, economic and political advantages. In
this section, trends of the usage divide in Taiwan and Hong Kong are
delineated (see the figures in Appendix 9.2), followed by comparison of
the usage divide in Taiwan and Hong Kong.3
Trends of digital usage
Searching for information has been the top reason for using Internet
services in Taiwan. The second most common Internet activities were
communication and online entertainment. The activity of online shopping
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The digital divide in China, Hong Kong and Taiwan 155
has been increasing in usage since 2004. Online banking and online
governmental services were used less than other activities in Taiwan. In
Hong Kong, the main purpose of using Internet services has been
searching for information and online communication since 2002. Clear
gaps between using Internet services for these two top activities and using
the Internet for entertainment and e-commerce purposes were shown.
The less common activities were online shopping and banking. Usage of
governmental services was generally low. In China, searching for
information, online entertainment and instant communication were
major Internet activities. Recent trends showed that searching for
information was the highest priority of Internet usage. The need for online
entertainment including music or video and online gaming has increased
over the past few years. Instant communication has outnumbered email
usage since 2007. The proportion of online users engaging in shopping
reached one third of Internet users and slowly increased over time. This
trend was followed by the usage of online banking in 2009.
A cross-regional comparison of the second order divide
The Internet offers a new range of usages to individuals; we adopt the
classification of Internet usage suggested by the UK digital inclusion study
(Helsper, 2008) to further compare the changes of these clusters of digital
engagement across regions. The first cluster is basic users of the Internet
who undertake practical activities such as information seeking, individual
communication and online shopping. Intermediate users are those who
use the Internet for participatory activities, including using government
services and online financial services. Since Internet activity by socioeconomic strata was only available in Taiwan and Hong Kong, Table 9.2
shows the trends of usage divides in these two regions.
For the basic Internet activities in Taiwan, the gender gap was shown to
be either disappearing or diminishing; males had a slightly higher
percentage in entertainment usage than females, while females had a
slightly higher percentage in online shopping usage than their male
counterparts. Age effects were generally declining in information
searching, communication, and entertainment; nevertheless, the youngest
group was far less engaged in information searching and the elder groups
were less engaged in online communication and entertainment. The gaps
between different age groups in online shopping activity persisted over
time. The gaps between usage of basic activities among educational levels
were either remaining or widening, except for online entertainment. In
general, educational differences still matter in digital engagement. The
effects of geographic location were gradually diminishing over time in
usage of basic Internet activities. The trend of digital engagement in Hong
Kong was similar to that of Taiwan. While the gender gap was
disappearing, the educational effects on searching for information and
The Digital Divide_BOOK.indb 155
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Declining except
the youngest
Persistent
Education
Declining
Region
Age
Persistent
Education
Disappearing
Declining except
in the youngest
Age
Gender
Disappearing
Gender
Declining small
gap
(M>F)
Entertainment
Small gap
persistent
(F>M)
Online Shopping
Persistent
Widening
Disappearing
Declining
Persistent,
widening in the
least educated
Declining
Widening
Declining small
gap
(M>F)
Declining
Declining
Widening**
Persistent**
Disappearing**
Modest gap
persistent
Widening
Declining yet gap Declining yet gap Persistent
persistent
persistent
Disappearing
Communication
*
Persistent
Persistent
Disappearing
Persistent
Widening
Widening
Disappearing
Online Banking
Persistent
Persistent
Persistent
Disappearing
e-Government
Intermediate Internet activities
*Communication in Taiwan is defined as instant communication; communication in Hong Kong is defined as communication with others.
**Indicates the activity of electronic commerce which includes online shopping and banking in Hong Kong.
Hong
Kong
Taiwan
Information
searching
Basic Internet activities
Table 9.2 Summary of the second order divide in Taiwan and Hong Kong
The digital divide in China, Hong Kong and Taiwan 157
communication were persistent. Moreover, age effects on online
communication and entertainment suggested that the usage gaps in these
two activities have widened among age groups. The trends of intermediate
level digital engagement demonstrated that age, educational level, and
geographic location continue to influence what people do online,
although the effect of gender has become irrelevant. The usage gaps of
intermediate Internet activities were either persistent or widening. These
results also suggested that a greater number of socio-economic factors
influence the use of intermediate applications than influence the use of
the Internet for basic activities. Far from the optimistic prediction, those
socially disadvantaged groups appear to be less included in the
participatory use of the Internet that could affect their life chances most.
On the contrary, those who are better off may benefit from the wider use
of ICT technologies and re-enhance their social, economic and political
advantages; digital divides thus lead to a deepening social inequality.
Discussion
The results of the cross-regional comparison of digital access suggested
that the Internet access gap was narrowing in highly connected regions.
However, after reaching the growing peak, the trend of the digital divide
in these regions was parallel to the lines of social divides. Those who were
most deprived socially, such as the elderly, less educated and the poor were
also the least likely to be digitally connected. The persistent gaps in
broadband and mobile access between high and low access populations
suggested that low access groups were again lagging in adoption of new
innovations. Moreover, for regions with rapid growth of digital access, the
main policy should be to address the unequal rates of diffusion in the low
socio-economic population. Without recognition of the unequal
accessibility within the population, the gaps of digital access will widen
and certain groups with social disadvantages will be at risk of exclusion
from various aspects of the information society.
The gaps between figures for men and women in both basic and
intermediate Internet usage have gradually improved. Regional gaps have
declined in basic usage, but persisted in intermediate activities. Age gaps
of online activity demonstrated different preferences between the young
and the elderly. Education matters across all online usages and activities
except for those recreational purposes. Less engagement in Internet
activities might be due to a lack of training and direct hands-on
experience. Along the lines of educational or ICT skills gaps, it is likely
that Internet use will be stratified, with some using it as an entertainment
device and some using it to seek and create new knowledge. Scholars have
suggested the Internet will not create knowledge seekers out of those
without the requisite background or skills (Warschauer, 2003). With more
advanced activity that requires high levels of skill capacity, not surprisingly,
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158 Shu-Fen Tseng and Yu-Ching You
the divides between people who have high and low educational levels were
persistent or widening.
Furthermore, the number of barriers to digital engagement was higher
for those intermediate activities than for basic uses of the Internet. A
greater number of socio-economic factors, for example age, education and
region, influenced the use of intermediate applications than influenced
the use of the Internet for basic activities. This result indicated an
intertwined link between digital engagement and social inclusion. Lack of
usage of needed resources will make groups that are already socially
disadvantaged fall further behind. On the contrary, individuals who
already have valuable resources, including material wealth and skill assets,
enjoy a privileged position to maintain their distinct advantages. Without
proper intervention, the wider usage of ICTs may become a potent tool to
deepen social divides and foster “the rich get richer” effect. These results
suggest that exploring how people engage in ICT activities and the
resultant impact on social exclusion is important in the current stage of
digital divide scholarship.
A narrowing access divide in Taiwan can be attributed to the active
government policy on bridging the digital divide. Several action plans
have been launched since 2003, such as providing digital TV signals and
reception devices in rural areas, connecting broadband networks to all
villages, establishing digital opportunity centers in all counties, supporting
small to medium enterprises to develop e-commerce, supporting digital
opportunity centers in Asia-Pacific Economic Cooperation (APEC)
economies and educating international trainers and professionals. While
substantial growth of digital access in the past decade was found, persistent
divides among the elderly, the least educated, and the poor in Internet,
broadband and mobile access suggested technological and social
disadvantages were inextricably linked. The growth of digital access did
not automatically solve social problems. Overcoming barriers to access
technologies in the socially disadvantaged groups requires active
government intervention. A shrinking gap between rural and urban areas
in Taiwan demonstrated a continued need for governmental policy to
support socially excluded groups in preventing digital disengagement.
As a result of open competition in the telecommunications market,
Hong Kong has shown that the pro-competition policy and pro-market
approach has been very successful in facilitating high penetration of ICT
development. Broadband Internet access in Hong Kong is among the
highest broadband penetration rates, and the number of mobile service
subscribers also represents one of the highest penetration rates in the
world. However, the persistent gaps in Internet access among the elderly,
less educated and economically disadvantaged demonstrated the need for
governmental policy to advocate for digitally excluded populations. Those
socially deprived are also the most at risk of lacking access to digital
resources. They are the elderly, the less educated with limited skills and
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The digital divide in China, Hong Kong and Taiwan 159
those with low socio-economic status. From the Marxist view of capital,
those who are already disadvantaged in terms of social and economic
resources are the most at risk of being excluded from the information
society. The inequality will deepen as they are deprived of the digital
resources and opportunities of engaging in online social, economic, and
political activities. As technology continues to develop, those who are not
included are at risk of being left further behind. Governments and other
stakeholders need to focus on tackling digital exclusion among the socioeconomically disadvantaged and bridging digital divides for these groups
to access the digital resources they need.
China has experienced exponential Internet growth in the last decade.
Despite the absolute number and percentage of Internet users having
increased dramatically, Internet penetration in China remains relatively
low when compared to the first tier digital nations. The slow increase in
usage rates of the elderly has lead to a widening trend of an age divide.
The trend shows a significant increase in the number of Internet users in
rural areas, nevertheless, the increase rates are behind those in urban
areas. The unequal distribution of Internet resources between segments of
the population has profound impacts on the continuation of social
inequality. While celebrating the huge growth of the Internet-using
population in China, policy concerns should respond to the widening gaps
of digital access and exclusion from digital engagement. The CNNIC
pointed out that the rapidly growing numbers of rural netizens have
become an important part of the new Internet population and most of this
rural population with a poor educational background has been attracted
to the Internet due to its recreational and entertainment functions
(CNNIC, 2008). From the aspect of digital inclusion, the low use of online
economic services and political functions let down the enabling power of
the Internet to enhance digital engagement and social inclusion. In this
regard, issues of wider uses of online functions and participatory activities
in China, such as education, learning, job seeking, e-commerce and
participating in public affairs should be addressed.
A relevant issue is Internet censorship. In China, only governmentapproved agencies and businesses are permitted to establish an Internet
Interconnecting Network and to license the operation of Internet service
providers at the next tier. All private Internet service providers are licensed
through one of these backbone networks and are required to install filters
to block undesirable content. In order not to risk having their licenses
revoked, most of these companies complied with the self-censorship
regulation in China (Liang and Lu, 2010; MacKinnon, 2008). Based on
the CNNIC reports, a great loss of search engine usage was found in 2006.
The downward trend in the usage of search engines might be a reflection
of the broader censorship in China on the bulletin boards, blogs, and
online news and information sites in the year of 2005. The usage of search
engines and news browsing functions decreased almost 15 percent
The Digital Divide_BOOK.indb 159
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160 Shu-Fen Tseng and Yu-Ching You
compared to the previous year. The number soon bounced back in 2007.
This resilience might be due to a huge infusion of Internet population
from the rural areas. Whether this downward trend of usage was due to
measurement problems or a reflection of governmental regulation, longterm impacts of Internet censorship on social and political change in
China deserve further investigation.
Currently, strategic responses to the digital divide by national, state,
and local programs often focus on getting more equipment and
connections, yet recent research has shown that it is insufficient to bridge
the divide by only responding to physical access need. Digital access is
essential, and interventions which provide access to the technology remain
important aspects of increasing digital engagement. In addition, human
resources, such as digital literacy, and social resources that engage in
meaningful social practices are also important to realize the possibility of
digital opportunity. From the Marxist perspective, this chapter contends
that social inequality might accelerate in the information society for those
privileged groups take uneven advantages and benefits from effective use
of the Internet in the social, economic, and political spheres. The lack of
effective digital skills and exclusion from the gains of the application of
technology in the socially deprived groups as compared to their
advantaged counterparts deepen social inequality in the information
society.
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The digital divide in China, Hong Kong and Taiwan 161
Appendix 9.1 Digital access in Taiwan, Hong Kong, and China
%
100
%
100
80
80
60
60
40
40
20
20
0
4
200
5
06
200 20
Individual
Mobile
Household
8
9
0
200 200 201
House.
Broadband
7
200
0
4
200
(b) Internet access by education level in
Taiwan
(a) Internet, broadband, and mobile
penetration in Taiwan
%
100
%
100
80
80
60
60
40
40
20
20
0
4
200
5
06 007 2008 009
2
200 20
2
<20K*
40~49K*
20~29K*
50~69K*
>=70K*
30~39K*
*: NTD
0
201
(c) Internet access by income in
Taiwan, 2005-2010
0
%
100
80
80
60
60
40
40
20
2 3 4
5 6 7 8
0 1
9
200 200 200 200 200 200 200 200 200 200
Household
Broadband
Individual
(d) Internet and broadband penetration
in Hong Kong
%
100
0
20
5 06 7 08
0
9
1
2 03 4
200 200 20 200 200 20 200 20 200 201
<=Primary
Secondary
Tertiary
0
2 3 4
0 1
5 6 7 8 9 0
200 200 200 200 200 200 200 200 200 200 201
<10K**
20~29K**
>=30K**
10~19K**
**HKD
(e) Internet access by education level
Hong Kong
(f) Internet access by income in
Hong Kong
%
100
%
100
80
80
60
60
40
40
20
20
0
6
7
08 009 010
200
2
200 20
2
<=Primary
S. high
J. high
University
5
200
5
4
2 3
0
6
7
8
9
200 200 200 200 200 200 200 200 201
Internet
Broadband
Mobile
(g) Internet, broadband, and mobile
penetration in China.
0
3
4
1 2
9
5
6
7
8
200 200 200 200 200 200 200 200 200
High school
M iddle school
and lower
College and
above
(h) Internet access by education level
in China.
Sources:
(a)(b)(c) Individual/Household Digital Divide Survey in Taiwan, 2004-2010
(d)(e)(f) Thematic Household Survey 2000-2009, Census and tatistics Department
of Hong Kong
(g)(h) Statistical Report on Internet Development in China, 2002-2010, CNNIC
The Digital Divide_BOOK.indb 161
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162 Shu-Fen Tseng and Yu-Ching You
Appendix 9.2 Internet activities in Taiwan, Hong Kong, and
China
%
100
%
100
80
90
60
80
40
70
20
60
0
6
4
5
200
200
200
Info. searching
communication
Entertainment
8
9
7
200
200
200
Online shopping
Online banking
e-Government
(a) Internet activities in Taiwan
40
6
8
7
5
200
200
200
200
S. high
<=Primary
J. high
University
4
200
9
200
(b) Information searching by education level
in Taiwan
%
100
%
100
80
80
60
60
40
40
20
20
0
004
2
005
2
6
200
7
200
<=Primary
J. high
8
200
9
200
010
2
0
S. high
University
(c) Online shopping by education level in. Taiwan
%
70
60
50
2
3
04 2005 006 2007 2008
2
200 200 20
Information
Entertainment
searching
e-Commerce
communication
e-Government
(d) Internet activities in Hong Kong
%
100
80
60
40
30
20
10
0
40
20
002
2
9
8
7
6
5
4
200 200 200 200 200 200
Tertiary
<=Primary
Secondary
2
003
(e) e- Commerce by education level in Hong Kong.
0
8
9
0
7
6
200
200
201
200
200
Search engine
Online
shopping
Communication
Online banking
Entertainment
5
200
(f) Internet activities in China
Sources:
(a)(b)(c) Individual/Household Digital Divide Survey in Taiwan, 2004-2010
(d)(e) Thematic Household Survey 2000-2009, Census and tatistics Department
of Hong Kong
(f) Statistical Report on Internet Development in China, 2002-2010, CNNIC. Note that
there is no “information searching” category in the survey, use of “search engine”
function is selected instead
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The digital divide in China, Hong Kong and Taiwan 163
References
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Castells, M. (2000). The rise of the network society, 2nd edition London, UK:
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Castells. M. (2001). The Internet galaxy: Reflections on the Internet, business, and society.
New York: Oxford University Press.
China Internet Network Information Center (CNNIC) (2008). Statistical Survey
Report on the Internet Development in China. Retrieved from http://www.
apira.org/data/upload/pdf/Asia-Pacific/CNNIC/21streport-en.pdf
China Internet Network Information Center (CNNIC). (1997–2010). Statistical
report on Internet development in China. Retrieved from http://www.cnnic.cn/
research/bgxz/tjbg/
DiMaggio, P., Hargittai, E., Celeste, C. and Shafer, S. (2001). From unequal access to
differentiated use: A literature review and agenda for research on digital inequality.
Retrieved from http://www.eszter.com/research/pubs/dimaggio-etal-digital
inequality.pdf
Hargittai, E. (2002). Second-level digital divide: differences in people’s online
skills. First Monday, 7(4), 1–19. Retrieved from http://chnm.gmu.edu/
digitalhistory/links/pdf/introduction/0.26c.pdf
Helsper, E. (2008). Digital inclusion: An analysis of social disadvantage and the information
society. London, UK: Department for Communities and Local Government.
International Telecommunications Union (ITU). (2010). ICT data and statistics.
Retrieved from http://www.itu.int/ITU-D/ict/statistics/
International Telecommunications Union (ITU). (2011). Measuring the information
society. Retrieved from http://www.itu.int/net/pressoffice/backgrounders/
general/pdf/5.pdf
Liang, B. and Lu, H. (2010). Internet development, censorship, and cyber crimes
in China. Journal of Contemporary Criminal Justice, 26(1), 103–120.
Lin, N. (2001). Social capital: A theory of social structure and action. New York:
Cambridge University Press.
MacKinnon, R. (2008). Flatter world and thicker walls? Blogs, censorship and civic
discourse in China. Public Choice, 134, 31–46.
National Telecommunications and Information Administration (NTIA). (1995).
Falling through the Net: A survey of the “Have Nots” in rural and urban America.
Washington, DC: US Department of Commerce.
Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet
worldwide. New York, NY: Cambridge University Press.
Research, Development, and Evaluation Commission (RDEC). (2002–2010).
Individual/Household digital divide survey in Taiwan. Yuan, Taiwan: Executive.
van Dijk, J.A.G.M. (2005). The deepening divide: Inequality in the information society.
Thousand Oaks, CA, US: Sage.
Warschauer, M. (2003). Technology and social inclusion: Rethinking the digital divide.
Cambridge, MA, US: MIT Press.
Witte, J.C. and Mannon, S.E. (2010). The Internet and social inequalities. New York:
Routledge.
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164 Shu-Fen Tseng and Yu-Ching You
Notes
1The Individual/Household Digital Divide Survey has been conducted
annually by the Research, Development and Evaluation Commission (RDEC)
(2002–2010), Executive Yuan in Taiwan since 2003. Take the 2010 survey, for
example, carried out through phone interviews with those residents of Taiwan
over the age of 12, with an effective sample size of 16,008 people.
2 The Statistical Report on Internet Development in China is conducted by the
China Internet Network Information Center (CNNIC) (1997–2010). The first
report appeared in 1997. Starting from 1998, the reports were issued twice a
year. The twenty-sixth survey, for example, was conducted in 2010, with a total
number of 30,000 residents at the age six or above interviewed by phone. Since
these reports only show proportions of netizens, we used the total number of
the population in each socio-economic category referenced by the National
Bureau of Statistics of China to yield percentages of Internet access in each
segment of the population. Usage of Internet services by Hong Kong residents
has been researched annually by the Census and Statistics Department of Hong
Kong since 2000 under its series of Thematic Household Surveys (THS). Some
10,000 persons aged ten and over in representative households were face-toface interviewed in 2010. The reports of this survey are compiled in the
Statistical Report on Internet Development in China.
3 Data of usage by socio-economic factors in China is not available in the CNNIC
reports.
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Section 4
Eastern Europe
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10 The Internet and digital
divide in South Eastern
Europe
Connectivity does not end the
digital divide, skills do1
Danica Radovanović
Belgrade Center for Digital Humanities
Introduction
The social paradigm of the information and communication technologies
(ICTs) has fundamentally changed many aspects of everyday life but ICTs
have also become an indispensable part of it. In this chapter, we take social
theories developed by the classical sociologists like Weber (1924), Giddens
(2006), and Meyrowitz (2008) and apply them to the issues of Internet
inequality. Weber’s stratification theory is grounded in the core
perspective on inequality, and we examine how access to the Internet
combines with variables such as class, status, education.
With this chapter, we are offering an understanding of social inequality
in the information-driven networked society and we are focusing on South
Eastern Europe (SEE) and on Serbia in particular. Serbia is an SEE
country in transition, and the political, economic, and social turbulence of
the 1990s have influenced its culture and ethical values, as well as the
development of the ICTs and the creation of an online public sphere
(Radovanović, 2010a, 2010b). The trends of Internet use in everyday life
did not pass Serbia by. The socio-economic and moral crisis in Serbia has
also reached the networked public and higher education.
It is not surprising that both the younger and the older generations in
urban areas have embraced the new social media forms very quickly as an
extension of their analog lives; but what about the necessity of new
literacies in the twenty-first century? How should they acquire necessary
skills that will enable them to use Internet services wisely and selectively, as
well as to best utilize the collaboration practices in the academic
environment?
We are all participating on a daily basis in a networked world and we are
the creators of the content online, in the same hyper-connected world
where the issues and patterns of social inclusion and exclusion need to be
observed and addressed.
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168 Danica Radovanovic
The goal of this chapter is to examine the paradox of how moving beyond
digital divides in the context of the technological infrastructure would
permit us to tackle other existing problems in order to explore the
differences in how the online public in Serbia use the Internet, not just in
their everyday lives, but also for learning, communication, and collaboration.
Some data in national and international reports on ICT use exists, but
not on the subject of Internet use and the digital divide in higher
education, and here we are trying to fill the gap in the existing reports and
data, and present some empirical findings that cannot be found in these
documents.
Finally, we indicate that there is a social stratification in regards to
Internet use, social media, and collaboration in higher education in
Serbia. The main empirical finding of the chapter has revealed the three
main factors of the digital gap, the categories of community/sociality,
participation and collaboration, as well as contradiction and its relation to
the theoretical points of stratification. Crucially, motivated high status
persons (professors at universities) are needed to advance digital literacy.
Ironically, it is those who have less influence (junior faculty, graduate
students, and undergraduate students) who are the savviest with Internet
technology. The high status persons have less motivation. But how can we
encourage the professors to adopt and use new ICTs? This is the
underlying conundrum, and the results raise some important questions
and shed light on current issues to be solved in the future.
Theoretical framework
Since we are examining stratification in the Internet from a sociotechnological and educational perspective, we decided that the Weberian
social stratification theory could be used as the theoretical approach for
this chapter.
Many studies on inequalities focus mainly on differences in socioeconomic backgrounds and in available resources, such as money or skills,
or they focus on developing inequalities such as access to basic human
resources including equipment, knowledge, or education. Those with
more access to resources “use their relative advantage to increase the
inequalities” (Meyrowitz, 2008, p.645).
Weber’s principles (1924) of status and class present a good starting
point for the Internet context of inequalities that are interconnected
within online communities and the exploration of the social media as
applied in educational communities. The access to produce information
and knowledge, or create and distribute the content online in the
information society, is stratified by socio-economic factors and skills or
literacy abilities. We examine two groups within the higher education
ecosystem in Serbia, in the context of status (or Stände) applying Weber’s
theory for analyzing Internet use.
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The Internet and digital divide in South Eastern Europe 169
In higher education, collaborative and communication processes
determine and form the category of status or prestige one holds within
one community. Conversely, outside academia, the possession of power is
more interconnected with the technological and economic infrastructure
that reflects the access to information, the Internet and computers (and
other devices that connect online), as it refers more to material goods,
social resources and the divide between the “haves” and the “have-nots”
(Warschauer, 2003). For example, possession of information or knowledge
can make one more powerful than others in society as one is in the
dominant position and can control the access to information or media.
These people are sometimes known as information gatekeepers. Social
power in the Internet perspective denotes the existence of status groups
that often show themselves in the form of communities sharing
information and knowledge, social media content, or other benefits within
likeminded groups online.
Internet access is a universal issue and of major concern to many
policy makers and governments. Opening up the access to knowledge
and its deployment in everyday work and education is crucial for
producing results and fostering the competences of students, scholars,
and knowledge workers. Access to information is the key to an
individual’s position in society; and still access is not everything, it is only
the starting point in many countries and societies while the present
power structures remain.
A communal action Gemeinschaft, according to Weber, is oriented to and
fueled by an “emotional feeling of the actors that they belong together”
(1924, p.150). Social networks and the networked sociality that people are
gathered around online today on the Internet confirm this function
within the Stände, i.e. defining one’s status in the community. People are
sharing in groups, gathered by some shared interest or purpose in a place
with others of their choosing where they feel they can belong and validate
each other.
On the other hand, on the issue of inequality, Giddens (2006) considers
as fundamentally important that education plays a significant role in
either strengthening or breaking down inequalities. Giddens argues the
role of education is critical as he identifies a new divide emerging between
those who have the opportunity to experience higher education and those
who do not. He thinks it is important not to think of the education system
as if it works in a vacuum – factors like changes in employment and the
economy also figure.
Thus having defined theoretical perspectives from classical sociology
that can help us understand and analyze the existence of a digital divide in
contemporary societies, we are going to describe the specific case of such
divides in Serbia in the rest of the chapter.
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170 Danica Radovanovic
Methodology
Statistical data about the digital divide exists and many reports have
considered who is and who is not online by gender, age, education, socioeconomic status, or region. This brief review cannot be comprehensive
about such broad topics, so we are focusing on higher education and the
use of the Internet and social media with available data and research
findings.
Most of the research on social inequalities with an Internet perspective
to date in Serbia has stayed on the level of analyzing data from national
and international statistical institutions, with the limitations of the study
lacking theoretical background and exploratory research in specific
environments. For example, no data was found in any report on Internet
use and inequalities within higher education in Serbia. While information
on Internet social media use in higher education has not been previously
published and was not available in those reports for Serbia, we did locate
individual Internet scholar research (Radovanović, 2010a, 2010b) that
discussed social media and social network use among young adults in
Serbia, and in higher education.
Data sources for the study, beside quantitative international indicators
from the reports, represent statistical data analyzed from the secondary
statistical sources. The Statistical Office of the Republic of Serbia (SORS)
telephone survey presents a sample of n=2400 households in the territory
of Serbia. SORS has been carrying out a panel study of Internet use in
Serbia since 2006, using the Statistical Office of the European Commission
(Eurostat)2 methodology.
We also present data from the semi-structured in-depth interviews
(n=32)3 with higher education representatives from the region (North,
Central, and South Serbia) with deeper insight into social media use and
collaborative processes online. The study population was young adults –
students (undergraduate and postgraduate) and teachers (professors and
junior faculty) who gave extensive feedback in conversations both face-toface and via telephone and Skype. Through exploratory and descriptive
analysis of the content from the transcripts we came to interesting
narratives expressed through offered input. Data from the interviews
represents the respondents’ opinions regarding the use of the Internet
and social media to illustrate the divide in communication and
collaborative processes in higher education, and social stratification
between these status groups.
International and national data on ICT use in Serbia
The latest SORS report of Internet use in Serbia was published in
September 2011 with data from surveys, providing a description of users as
well as their socio-economic background. Internet usage is analyzed based
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The Internet and digital divide in South Eastern Europe 171
on the penetration, type and frequency of Internet use, education and
employment status. Internet penetration presents one of the key indicators
related to widespread information society development. According to the
Internet World Report statistics as of June 2011 (Internet World Stats,
2011), in Serbia there were 4,107,000 Internet users which represents a 56
percent Internet penetration, according to the ITU (International
Telecommunications Union), and 2,866,200 Facebook users on June 2011,
indicating a 39.2 percent penetration rate.
However, the SORS survey shows that social-economic factors are the
main issue, and the correlation between the use of the Internet and the
income of the user demonstrates a significant gap in usage rates
depending on income level. Another evident divide is between rural and
urban households with relation to ICT use, almost double in percentage
for urban populations with 60.8 percent versus 39.7 percent for rural
populations.
In Serbia 52.1 percent of households own a computer or Internet
capable device, 50.6 percent of the users have a DSL connection, while 7.8
percent still use modems to get online, and 29.6 percent use cable Internet
(SORS, 2011, p.18). The share of Internet users is linked to level of
education: 73.8 percent of individuals with a university degree use the
Internet, as compared to 57.4 percent of those with secondary school
education and 17.7 percent of individuals with an educational level lower
than secondary school.
There is only one information source in the SORS survey on social
media usage among the population and it is based on the sole variable
“types of Internet use.” Respondents who used the Internet reported it was
mostly for participation in social networks (69.8 percent). Also, 91.8
percent of the Internet population aged 16–24 has one or more accounts
on Facebook and Twitter, which indicates that the most frequent users in
Serbia are young adults, and most of their Internet time is spent on social
networks. They use the Internet for education purposes as well, with 65.5
percent reporting that they search for information relating to education as
well as browsing Wikipedia (45.5 percent).
In regards to e-learning and digital literacy, the survey (ibid., p.32)
showed that only 5.6 percent of respondents had attended a course on
using computers in the last three years. A surprising 79.7 percent of them
said they had never attended any course. However, according to the UNDP
Human Development Report (2010), the list of the Balkan countries by
literacy rate places Serbia in sixty-fifth place (96.4 percent literacy rate).
This report indicates that Serbia belongs to the high human development
group, and as for education, it is interesting that there is no data on the
adult literacy rate ( Human Development Report, 2010, p.145).
With regard to the utilization of ICTs within education, computers and
access to the Internet: 100 percent of primary and secondary schools have
computer labs and 87 percent of schools have Internet access which is an
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172 Danica Radovanovic
average of 26 pupils per computer (eGovernance and ICT Usage Report
for SEE, 2010, p.54). It is interesting that the curriculum for ICT skills and
obtaining digital literacy is optional and that computer science is not a
mandatory subject in primary schools, while in the secondary schools it is
mandatory from the first or second grade, depending on the school’s
educational profile (ibid., p.57).
As for ICT use in higher education, there is no data available for very
important indicators, such as the number of students per computer at a
typical university, or the percentage of male and female student users or
how often they use the Internet. It is unfortunate that this important
information is not available officially and the lack of research and data
should be addressed seriously by governments, higher education
institutions and ministries. Moreover, the digital literacy among scholars
and the monitoring of the intellectual potential in the ICTs should be
improved through the further development of national academic
networks, as well as the improvement of regional networks and educational
interconnections.
Online collaboration and digital divide in higher education
A good educational system should have three purposes: it should
provide all who want to learn with access to available resources at any
time in their lives, empower all who want to share what they know to
find those who want to learn it from them; and, finally, furnish all who
want to present an issue to the public with the opportunity to make
their challenge known (Illich, 1971, p.75).
As Internet technologies are rapidly evolving, new digital divides on the
Internet emerge. In this section we move the initial concept of digital
divide toward the focus in its transition from a technological to a social
context (Warschauer, 2002), and focus on social media use, digital literacy
skills, and collaboration in higher education in Serbia. Weber’s social
stratification theory focuses on access to production rather than
ownership of the capital of one’s production. In doing so, access to
production, in this context, is access to the Internet and e-resources in
order to produce information or accomplish interaction. Those without
access to the Internet cannot participate in collaboration, production, and
education processes. Weber was right about social stratification given that
the digital divide creates new boundaries. Besides basic social stratification
from a lack of computers or Internet access, we can also consider a
knowledge gap, and digital literacy skills. Having Internet access does not
necessarily mean that one group will use it wisely or use its resources in a
smart way. For example, if a group does not possess some amount of digital
literacy skills, how would they know how to use browsers for research, or to
edit a Wikipedia article?
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The Internet and digital divide in South Eastern Europe 173
In Serbia Internet access is not the major problem (Accessing and
Disseminating Scientific Information in SEE, 2005, p.23). The challenges
are different. For example, within the academic community, students and
researchers complained that e-resources were not available, when in fact
there are over 35,000 scientific journals available. We have the paradoxical
situation of e-resources not been being used at a satisfactory level due to
many factors and challenges. Among these challenges is a lack of awareness
and promotion, digital illiteracy and other human and economic factors
indicated by the knowledge gap.
Using Weber’s concepts, we can relate to his principle of Gemeinschaft
with collaborative networks of knowledge in education (Illich, 1971). They
are communities in the sense that they differ from “societies” in which
links between people are purely rational and extrinsically motivated. In a
community, according to Weber, there is something more affective and
personal which is an adequate context for online networks. If we look at
the dynamics of online communities and social networks where
communication and education processes are emerging, we find that
people (re)connect, interact, “like” statuses, seek validation, and dozens of
other things while constantly communicating and participating online.
However, by participating and creating the online public sphere, they also
learn, through the processes of socialization. They use e-resources for
learning and education.
These social and communication practices – networking, collaboration,
and interaction between groups who commonly use the Internet and social
media in Serbia – are examined with regard to professors and students. In
the Weberian stratification context we have two status groups from the
academic community: they are stratified by the status of their respective
roles. From the qualitative research data we analyzed, professors are more
concerned with technological infrastructure, human relationships,
Internet adoption and other problems while students are more concerned
with the lack of professors’ feedback via digital means and their willingness
to adopt social media, illustrating the gap in the communication and
collaborative practices between the two groups.
Here is what some respondents in the semi-structured interviews had to
say:
I think the lack of financial resources in academic and in individual
frames is one of the key factors for the modest application of ICTs.
Also important is the indifference of teachers (from primary school to
university). One should not only observe the situation in Belgrade and
other large cities (which is also not great), but also examine the
situation inside Serbia (Nikola, professor).
DiMaggio and Hargittai (2001) point out that social inequalities influence
digital literacy, engagement in social and educational life, and overall
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174 Danica Radovanovic
participation and collaboration in an online public sphere. We have
marginalized groups who will not have access to the Internet and therefore
are not going to be able to engage in this social life and those without the
necessary networked literacy skills to navigate online. Professors
concerned with equipment and implementation of software in teaching,
think that “the Internet should be accessible to everyone and in every place
at the universities, and that is not always the case, for now.”
Besides the technological challenges, professors indicate other
obstacles for collaboration and participation, including lack of motivation,
problems with the staff in academia, interpersonal relations, and
corruption in the academic community:
The conditions are not the same in developed and underdeveloped
cities. Schools are unequally equipped; teachers are unevenly trained
and motivated. A lot depends on the Director/Dean of the institution
(Marko, junior faculty).
Unfortunately, in an environment where I work, there are personal
and unscientific reasons. In my faculty, the Dean has created
unhuman relationships, everything is subordinated to the whims of
the Dean’s Office, and the Ministry of Education does not care.
Collaboration takes place in personal relationships (Vesna, Professor).
We also examined the possibilities of Internet usage and social media in
the learning environment as a tool for collaboration and participation that
encourages and fosters communication processes and decreases the
widening gap. There were communication and collaboration issues
detected among professors and students.
Respondents indicated that neither group was satisfied with the
participation and communication levels of their colleagues.
Professors are very inflexible on many issues. We study from the
same books for ages and in my field of study things are changing
every day. There are fewer practical examples than there should be. I
think the key point is to convince the professors to do their job, and
their work is “to promote and disseminate knowledge.” The professor
has to be a leader in that sense, the first one to have an account, to
create a group that supports the dissemination of information and
knowledge, and not to hide them from their students (Natasa,
postgraduate student).
Despite not being satisfied, professors and students agree that it is possible
to initiate and foster collaboration by the introduction of the Internet and
social media services into classrooms and curricula. Professors believe that
by the promotion of education platforms for collaboration and learning,
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The Internet and digital divide in South Eastern Europe 175
along with the introduction of “distance learning” and formalization of
the e-courses, the present levels of collaboration can improve.
When we talk about new literacy requirements (Haythornthwaite,
2007), we include competencies related to the set of skills required of an
individual in order to perform tasks that include finding, processing,
producing, and communicating information as well as fluency in online
technologies, communication norms, application, and programming
environments.
Students think that “professors must know how to use new platforms
and be leaders in that, rather than waiting for the initiative from the
students.” In the first place students emphasize education and training as a
major factor – for both status groups – in order to use these services and
obtain the necessary set of skills:
Education for professors to use social media (at the state universities)
is needed as the initiative must come from them. Moreover, some of
the tools should be accepted at the institutional level and all professors
should be obliged to use them.
Also, students believe that collaboration is possible by enabling access to
the Internet and the content. They report that the Internet in classrooms
and “computers for each of them, for each student” is crucial. Accessibility
of the resources is possible “by uploading more content on the web, where
the information could be easily accessible, creating the networking
capability for remote collaboration.”
Some scholars do not think it is possible to initiate and foster
collaboration by using Internet services and social media. Some professors
have said that “it is too demanding, and students are changing.” Others
state: “the older generations of professors are still not educated and
trained to communicate electronically, and are therefore not able to use
this medium.”
Professors have also expressed the following opinions and feelings:
uncertainty (“I do not know how our students would accept new
technologies”), doubt (“I’m not sure if they would be interested in this
kind of collaboration”), and concern (“There is low awareness about the
possibilities of implementing social media sites for collaboration”). Other
professors also commented on the motivation of their colleagues
(“willingness of both sides is needed to make a contact using this form of
communication”), lack of initiative from both sides, then “insufficient
education of colleagues” and “maybe even fear of the new,” as important
issues affecting the acceptance of new technologies to enhance
collaboration and participation in the academic community.
When it comes to the potential improvements to be gained by the
higher education community through ICT implementation that would
facilitate and encourage collaboration, professors state that there should
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176 Danica Radovanovic
be initiatives within the faculty as well as “new and improved policies for
ICT use in education,” while, students consider “open and frequent
communication between teachers and students” as a very important factor.
Both groups agree on the need for promotion and organization of courses
for students and teachers on digital literacy.
As regards the question referring to the limitations of the current
education system, related to Internet use, respondents have indicated
strongly that the lack of initiative in the faculty to implement these
services and present them to students is a hindrance. Also, respondents
(both professors and students) said that professors are not interested in
participating and accepting the new software and web technologies.
They “lean towards the older, traditional ways of communication and
learning.”
It seems that in the omnipresent social networking surroundings there
is an unbalanced momentum between these status groups, where students
are more prepared than professors to use Internet services and social
media. On the other hand, it strongly depends on the willingness and the
motivation of professors to adopt and adjust to new ways of interacting
with students. Though there is a hope of junior faculty who have already
embraced digital technologies, implementing them in the classroom, and
communicating online with students. Not all universities are equipped but
again the above statistics show that over 50 percent of the population is on
the Internet and Facebook, and those are students, so maybe a solution is
to look for the future collaborative practices among these two status
groups via places where students spend most of their time – and those are
online habitats.
Thus our main empirical finding has revealed factors of the digital
divide in the academic community, related to the stratification theory and
the Weberian concept of status (Stände) and social power between two
groups. We now turn to the possible recommendations for solutions which
might lessen the digital divides.
Conclusion and further recommendations
The results provided in the statistical and qualitative analyses above show
relationships between socio-economic factors and Internet use. We
presented some empirical data that cannot be found in the international
and national reports to indicate the importance of collaborative and
participatory possibilities for bridging the digital divide.
According to the results of this research, two status groups – professors
and students – agree that the ministries are demonstrating a lack of
initiatives for the implementation of ICTs and that they should encourage
a change in the higher education system in Serbia. A lack of policy and
action related to digital literacy could lead to even higher digital divides
and inequalities among different social groups.
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The Internet and digital divide in South Eastern Europe 177
This chapter indicates that besides the unequal access to the Internet
and computers, there is a social divide as regards Internet use, a lack of
twenty-first century literacies, a knowledge gap, and communication and
collaboration issues between the two status groups in the context of
Weberian stratification theory.
The main empirical evidence has revealed the three main factors of the
digital inequalities as a growing phenomenon in the academic community
in Serbia. Those are the categories of community/sociality, participation
and collaboration online, as well as the contradiction and its relation to
the theoretical points of stratification. Crucially, high status persons
(professors at universities) need to learn and adopt social media and new
technologies in order to advance digital literacy. They need to implement
and encourage the use of Internet services and web sites that would enable
collaboration and communication amongst other colleagues and students.
Ironically, it is those who have less influence, and social power according
to Weber (junior faculty, graduate students, and undergraduate students),
who would be savviest with ICTs. The high status persons have less
motivation. How can we encourage the professors to adopt and use new
ICTs? This is the underlying conundrum, and the results raise some
important questions and shed light on current issues to be solved in the
future.
Collaborative possibilities using the Internet and social media present
one of the most engaging opportunities for overcoming inequalities in
twenty-first century literacies and fostering better collaboration and
participation in higher education environments.
National government institutions should play a key role in developing,
implementing and promoting a consistent higher educational policy that
would encourage a wider use of the Internet in higher education. Future
research will show if new improved and implemented policies will facilitate
bridging the social stratification online, in order to decrease the existing
digital divides.
References
Accessing and Disseminating Scientific Information in South Eastern Europe
(2005). UNESCO. Available online: http://unesdoc.unesco.org/images/
0015/001532/153225e.pdf (accessed 11 October 2011)
DiMaggio, P. and Hargittai E. (2001). Digital inequality: From unequal access to
differentiated use: A literature review and agenda for research on digital inequality.
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influence. Journal of Communication, 58(4), 641–663.
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друштвених мрежа: Фејсбук и млади у Србији (Internet paradigm, structure,
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Notes
1 The author acknowledges the assistance of Mr. Baudry Rocquin, D.Phil. in
History, University of Oxford.
2 In Europe, Eurostat conducts surveys and publishes reports, including ones
related to Internet use.
3 Respondents come from state and private faculties in the territory of the
Republic of Serbia. The semi-structured interviews occurred in March 2011
and March 2012.
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11 Closing the gap, are we
there yet?
Reflections on the persistence
of second-level digital divide
among adolescents in Central
and Eastern Europe1
Monica Barbovschi
Masaryk University
Bianca Balea
Babeş-Bolyai University
Introduction
In spite of the initial enthusiasm about the Internet’s capacity to facilitate
access to information and thus expand access to education, jobs and
better healthcare, research showed, very early, that the new technology
exacerbates inequality rather than ameliorates it (DiMaggio, 2001). It
became increasingly obvious that access to the Internet is dependent on
various characteristics such as socio-economic status, gender, race, age,
and ethnicity, and these differences are likely to reinforce inequality in
opportunities for economic mobility and social participation (DiMaggio
et al., 2004). Arguing that mere access is not enough to ensure equal
take-up of opportunities, the theorists of the second-level digital divide
(Hargittai, 2002) tried to move the debate onto factors of digital
inequalities from a technological deterministic view of material access,
to social and cultural factors that shape patterns of use (Selwyn, 2004).
In addition, the conflict perspective of digital inequalities states that
without the development of Internet competencies, as a particular set of
skills, access to the Internet may in fact foster enduring social inequalities
(Witte and Mannon, 2010).
In line with the “emerging digital differentiation” (Peter and
Valkenburg, 2006), we expected the patterns of digital inequality to be no
less relevant for children than they are for adults and that socioeconomical and digital inequalities among adults (parents) would
reinforce/perpetuate digital inequalities among children. As in the case
of adult users, significant differences can be found in the way children
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180 Monica Barbovschi and Bianca Fizeşan
access and use the Internet, as indicated by research that has tried to
debunk the myth of the monolithic image of the techno-savvy child
(Livingstone et al., 2005). Demographic variables, breadth and depth of
Internet use were expected to play a role in accounting for differences in
children’s digital skills. In addition, parental socio-economic status and
demographic variables, along with variables of parental Internet access
and use were expected to influence children’s Internet access and use, as
well as their digital skills.
The EU Kids Online data confirms that within the 25 European
countries, children differ in their level of digital skills, regardless of
whether it is measured by self-reporting, the range of online activities or
the beliefs in their Internet abilities, which points towards a second-level
digital divide (Hasebrink et al., 2011: 30). Moreover, children in Romania
and Bulgaria (both countries with low GDP and recent introduction of
broadband) report both the highest levels of Internet use and a very low
range of online activities and digital skills as reported in Lobe et al. (2011),
which might be an indicator of digital inequalities. These countries
seemed to be perfect examples of second-level digital divide, where access
is available, usage is high, but the differences in opportunities taken
online, digital skills and, consequently, benefits are still widespread. For
comparison purposes Poland was chosen as a country with high use, while
Hungary was chosen as one of the countries with low Internet use among
children. At country levels, GDP per capita and broadband penetration
had no influence on children’s Internet use (Lobe et al., 2011), therefore,
we looked at the individual level in order to account for the differences.
However, the number of education years was a relevant national indicator.
The fact that data from all four of these countries demonstrated cases of
“digital natives,” with children’s Internet use surpassing that of their
parents, was also noteworthy.
Building on the data from the EU Kids Online II project (2009–2011),
the chapter explores the difference in access, use and skills among
adolescents (aged 11 to 16) in four Central and Eastern European (CEE)
countries, namely Bulgaria, Hungary, Poland and Romania, under the
assumption that these differences might still be attributed to socioeconomical inequalities (Witte and Mannon, 2010).
Literature review
Two dominant perspectives have emerged in the attempt to understand
the connection between social categories and digital inequalities:
enthusiasts of the digital revolution, who prophesized a relationship
between the increase in level of access and a decrease of the digital gaps
(Howard et al., 2001; Norris, 2001) and pessimists, who foresaw deeper
divides appearing (van Dijk, 1999; van Dijk, 2005; DiMaggio, 2001;
Hargittai, 2002; Katz and Rice, 2002; Wellman and Chen, 2005).
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Closing the gap, are we there yet? 181
According to the latter, the differences in the way we use the Internet go
much deeper. Hargittai and Zillien (2009) highlight that individuals
cultivate different forms of Internet practice depending on their socioeconomic background. Individuals with high status are much more likely
to engage in capital-enhancing activities2 online and subsequently, to reap
more benefits from their time spent online than users from lower socioeconomic backgrounds. Scholars like DiMaggio (2001; DiMaggio et al.,
2004), Hargittai (2010) and Zillien (Hargittai and Zillien, 2009), Wellman
and Chen (2005), and van Dijk (2005) have advanced original theoretical
models for the studying of digital divides which include differences in
equipment, autonomy of use, social support, skill, and the purposes for
which one is using the Internet (DiMaggio et al., 2004; Hassani, 2006 as
cited by Hargittai and Hinnant, 2008).
Another model advanced by van Dijk (2005) takes into account a
number of personal and positional categorical inequalities in society, the
distribution of resources3 relevant to this type of inequality, a number of
types of access to ICTs and a number of fields of participation in society.
The relationship between these factors can be summarized as follows:
personal and positional categorical inequalities in society produce an
unequal distribution of resources, which leads to an unequal access to
digital technologies, causing unequal participation in society, which
reinforces categorical inequalities, and unequal distribution of resources.
In other words, as one gap closes, another one opens, pointing towards a
rather dystopian view of social inequalities.
Adolescents and the digital divide
Most studies have shown that traditional measures of inequality – age,
gender, socio-economic status (SES) – influence access, use and online
skills. However, few have been preoccupied with the differences in digital
access, use and skills among children and adolescents. These few studies
(e.g. Livingstone et al., 2005; Livingstone and Helsper, 2007), however,
suggest that demographic factors directly influence young people’s
experience of both online opportunities and risks. Older children, it
seems, both take up more opportunities (educational, civic,
communicative, creative, etc. [see Livingstone et al., 2005]) and encounter
more risk. Also, there is evidence that those from higher SES homes not
only have better Internet access, but also take up a greater range of
opportunities online (Kaiser Family Foundation, 2005; Livingstone and
Helsper, 2007). According to Livingstone and Helsper’s study (2007), SES
has no direct influence on either opportunities or risks, but only
influences access, resulting in inequalities that have indirect but
significant consequences. The policy implications were intriguing; while
middle-class parents often provide better access for their children, for
those middle- and working-class children with equivalent access, there are
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182 Monica Barbovschi and Bianca Fizeşan
few or no direct effects of SES on use, literacy or opportunities. Enhancing
quality of access (i.e. more sites of access, more private use) for less
privileged teenagers could, therefore, reduce the digital divide among
young people (Livingstone and Helsper, 2010).
In addition, a “rich get richer” model of online communication (Kraut
et al., 2002; McKenna et al., 2002) can envision the development of skills
as a consequence of a more intense communication pattern. In their
study on Dutch adolescents aged 13 to 18, Peter and Valkenburg (2006)
pitted the perspective of a disappearing digital divide against the
perspective of an emerging digital differentiation and found support for
the latter. They advanced the prediction that teenagers with more socioeconomic, cognitive and cultural resources will use the Internet more as
an information and social medium, while less advantaged adolescents
will mostly use the Internet as an entertainment medium. This appears
to be the case for Romanian and Hungarian teenagers in the EU Kids
Online study, since they engage mostly in entertainment activities rather
than in creative, advanced uses (Hasebrink et al., 2011).
Moreover, since educational background is related to the integration of
digital technologies in the daily lives of individuals (Bonfadelli, 2002;
Korupp and Szydlik, 2005), we can expect that the educational level of
parents has an influence on how their children make use of these digital
technologies.
Drawing from the same perspective, we would expect to see some
relationship between types of Internet use and class position/class
background (Witte and Mannon, 2010: 84), since “conflict” theorists argue
that class inequality is reproduced across generations. Another interesting
concept, “the sedimentation of racial inequality” (Oliver and Shapiro,
1995), offers a similar understanding of the perpetuation of digital
inequalities from one generation to another. This chapter aims to
contribute to our understanding of the phenomenon of digital
“stratification” and inter-generational digital inequalities, in a region
where these differences are expected to matter most.
The EU Kids Online project (2009–2011) has showed, beyond any
doubt, that most children are fully online at an increasingly earlier age.
The findings presented in Livingstone et al. (2011); Lobe et al. (2011);
and Hasebrink et al. (2011) offer detailed accounts on patterns of access,
use and skills among children aged 9 to 16 across Europe. Half of
European children use the Internet from a private room at home and
older children spend nearly two hours online every day (Livingstone et
al., 2011). Among the findings that are relevant for this chapter are:
private use is strongly differentiated by age and the education of the
household; more various and sophisticated access and use is
differentiated by SES and education; children are further differentiated
in terms of breadth of online activities, which points towards a “ladder of
opportunities” influenced by age, gender (boys conduct more online
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Closing the gap, are we there yet? 183
activites) and parental education. Digital literacy skills and safety skills
also differ by age, gender (boys declare more) and parental education
(Hasebrink et al., 2011: 22–23, 27).
Among the four countries investigated, the differences are strongly
marked: in terms of locations of use and devices for accessing the
Internet, all reported below average figures (Lobe et al., 2011: 23).
Bulgarian children have the highest number of average skills (4.7) and
highest number of reported activities (7.8), followed by Poland with 4.5
and 7.1 respectively, then Hungary and Romania (both scoring 3.4
average skills, and 7.5 and 7.3, on online activities respectively). The
European averages were 4.2 for skills and 7.2 for activities (Lobe et al.,
2011: 26). If we look in the ladder of opportunities at “advanced and
creative uses,” Poland and Romania have the lowest levels among all
European countries (15 and 14 percent), while Bulgaria and Hungary
have quite high levels, (27 and 33) compared to the 23 percent European
average.
Our research questions, inspired by the ideas advanced by Livingstone
and Helsper (2007), are related to the three perspectives taken into
consideration: children’s emerging digital differentiation, the conflict
perspective and the inter-generational transfer of digital inequalities:
1 Is there a digital divide among adolescents in CEE countries? If so,
what role do age, gender and type of Internet use play in the digital
skills of adolescents?
2 Does the parental digital divide perpetuate the digital divide among
children?
3 Does the parental background perpetuate the digital divide among
children?
Our analytical model
Four major types of variables were employed to explain differences in
digital skills and confidence in Internet use for children in Hungary,
Romania, Poland and Bulgaria. A first set of parental background
variables was included in order to establish a “class positioning” or
parental background. Second, another set, related to parental Internet use
and level of support for various online activities of the child, was included.
The child demographics were also taken into account and last, variables
related to children’s access and use were introduced. Also noteworthy, the
two types of dependent variables, confidence in one’s Internet abilities and
digital skills (or competencies) of children are all interdependent with
children’s online activities.
The digital skills of children included in the questionnaire can be
divided into what van Dijk and Hacker (2003) call instrumental and
informational skills (for detailed description, see Hasebrink et al., 2011).
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184 Monica Barbovschi and Bianca Fizeşan
While we can assume that more activities lead both to more confidence
and more skills, building up more skills and more confidence also works as
a facilitator for taking up more activities (opportunities) online. Therefore
a causal link is difficult to pinpoint. Based on these assumptions and on
previous literature, we propose the following analytical model, with all
four sets of predictors having direct and indirect influences on the
dependent variables (Figure 11.1).
Concretely, the analysis was driven by the testing of the following
hypotheses:
H1. In line with the “emerging digital differentiation” and the “rich get
richer” model, we expect inequalities in confidence and skills among
adolescents, even if they all have access to the Internet. Specifically, we
expect that differences in private use, number of years online and range
of activities undertaken online will account for differences in confidence
and skills.
H2. In line with the conflict perspective, we expect that differences in socioeconomic status/educational background will account for differences in the
range of activities undertaken online and range of digital skills developed
by adolescents.
H3. According to a model of “inter-generational digital transfer”, we expect that
parental usage influences the children’s digital outcomes (confidence and
skills).
Parental background
(Education level)
Parental usage
and attitudes (confident
use, support given
to child)
Children’s online
competencies and
confidence in use
Child demographics
(Age, gender)
Child usage
(Years online,
private use, activities
online)
Figure 11.1 Analytical model for children’s digital competencies and confidence in
own Internet use in Bulgaria, Hungary, Poland and Romania.
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Closing the gap, are we there yet? 185
Method
The EU Kids Online project collected data from a random stratified
survey sample of 1000 children and one of their parents in each
participating country. For the purpose of our study, only responses from
children 11 to 16 years old in the four countries were taken into account
(N=3154). The sample includes 48 percent girls and 52 percent boys with
an average age of 13 years (SD=1.7). Our analyses included two types of
dependent variables: children’s confidence in their use of the Internet
(child confident use, or children’s belief in their Internet abilities, in
Hasebrink et al., 2011) and their digital competencies or skills (online
competencies).
The variables used in our analyses were grouped in four categories:
independent parent related; intermediate parent related; independent
child related; and intermediate child related (Table 11.1).
Correlations among all variables entered in the analytical model
revealed systematic relations between demographic variables of parent
and child, parent’s Internet use, child’s Internet access and use, and
finally, the child’s online activities and competencies.
However, in order to account for causal effects between variables, a
path analysis was conducted with AMOS. In order to control
multicollinearity problems,4 we decided to include the highest level of
education in the household instead of SES (since SES was derived from
the education and occupation of the household main wage earner), even
if the same relations were observed when using SES. Following the
previous literature and based on the correlation indicators, some
relationships were hypothesized (such as the link between use and
confidence in personal use, or use and skills); also, following the logic of
second-level digital divide and inter-generational digital transfer, we
expected significant relationships between parent-related variables and
intermediate children-related variables, on one hand, and the dependent
variables, on the other hand.
Analyses and results
The correlations indicators suggest that older teenagers and boys have more
years online than girls, engage in more online activities, are more confident
and report more online competencies. Children from more privileged
backgrounds receive more support from their parents, are more confident
in their usage, are online longer, experience greater private use, and also
display more digital skills than the less privileged children. But it is not only
demographics variables that create differential usage. There are significant
correlations between intermediate variables as well. More time spent online
and the possibility to use the Internet in a private manner can also affect the
way children use the Internet.
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186 Monica Barbovschi and Bianca Fizeşan
Table 11.1 Descriptive statistics of variables employed
Variable type
Mean Standard Description
Deviation
Independent
parent related
Education
level
Independent
child related
Intermediate
parent related
Intermediate
child related
Dependent
variables
4.2
1.2
Highest education level
completed by the head of the
household.
Age
13.4
1.72
Scale variable, 11–16 years old.
Gender
—
0.5
Dummy, Female=0.
Parent
confident use
0.7
0.4
Dummy, Confident=1.
Parental
support
5.7
3.2
Range 0 to 11, calculated from
“Yes”
responses to the question “Which
of the following things, if any, do
you sometimes do with your
child?” Eleven activities listed,
such as talking to the child about
what he or she does on the
internet. Full list in Hasebrink et
al. (2011).
Years online
3.9
2.07
Number of years online, scale
variable, Highest=13.
Private use
0.6
0.4
Private use from the bedroom
and/or mobile. Dummy variable,
Yes=1.
Online
Activities
7.3
3.3
Scale variable, the number out of
16 possible activities, such as using
the internet for schoolwork or
visiting a chat room.
Child
confident use
0.8
0.3
“I know lots of things about using
the internet.” Dummy variable,
True=1.
Digital
competencies
3.9
2.6
Scale variable, the number out of
8 in total.
Figure 11.2 presents the causal paths between our variables, for all four
countries, with the significant path (beta) coefficients.
In the European dataset, activities, skills and children’s belief in their
Internet abilities are all positively associated (Hasebrink et al., 2011: 30).
This remained true, unsurprisingly, in our general model and at country
levels as well: children with higher activity on the Internet become more
confident and more skilled.
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Closing the gap, are we there yet? 187
Parent
confident
use
.20
Education
level
-.09
.19
Parent
support
.21
-.18
-.05
.13
.28
.08
.33
Child’s
age
.16
Years
online
Children
confident
use
.15
Online
activities
.06
.23
.36
.08
.05
.17
.07
Gender
.14
.10
.17
Private
use
.15
.06
Children’s
online
competences
Figure 11.2 Path model for children’s digital competencies (skills) and confidence
in own Internet use in Bulgaria, Hungary, Poland and Romania
Source: EU Kids Online dataset, own Path analyses; Base: all children 11–16 in Bulgaria,
Hungary, Romania and Poland who use the Internet; all path coefficients significant at
p < .01 and p < .05 levels. The model fit was considered acceptable based on the following
indicators for complex models: RMSEA values=.046 (with a confidence interval .812) and a
CFI value=.970. The value of chi-square (χ2 (16) = 121.7 significant at p < .01) isn’t relevant
since chi-square values are known to be very sensitive to large sample sizes (Kline, 2005).
The model is confirmed for each individual country.
First, as predicted in our first hypothesis, the analysis revealed a
differential usage pattern for the children 11 to 16 years old who use the
Internet. Both parent and child-related variables have significant
influence on children’s digital outcomes. Moreover, parents with higher
educational backgrounds are more confident in their use and provide
more support for their children, which in turn increases their online
competencies. However, older children have less confident parents and
receive less support from their families, which is to be expected with the
increasing autonomy of adolescents and their gaining more confidence in
using the Internet. Conversely, the more the parents know about and use
the Internet, the less children report confidence in their own use.
Regarding child-related variables, boys display more Internet selfconfidence than girls, regardless of parental background or Internet
usage. Moreover, older children and boys are more experienced than
younger children and girls, are online longer and are engaging in more
online activities, also becoming more confident and skilled. In terms of
the “rich get richer” paradigm, our analysis sustains that more privileged
children are using the Internet for a longer time and more privately, which
helps them rally more online activities and also develop more confidence
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188 Monica Barbovschi and Bianca Fizeşan
and more skills. This might be a late effect of the first-level digital divide,
with parents in more privileged positions having been able to offer earlier
Internet access to their children.
Parents from higher SES households are also more active in terms of
giving advice about use and safety (since they are more likely to be users
themselves and more technically competent, according to Hasebrink et al.,
2011: 12). In our analyses, parents’ education is a predictor for their
confidence in Internet use as well as for the amount of support given, which,
in turn, work as predictors for their children’s Internet competencies.
Country-specific results
As in the general model for all four countries, in the case of Romanian
teenagers (χ2(16)=42.46, CFI=.97, RMSEA=0.047), age holds a direct
relation with all dependent and independent variables, while gender has a
slight influence on children’s years online (boys generally having more
than girls). The influence of parental support is higher for Romanian
teenagers when it comes to their online competencies, but has no
influence on children’s confident use. Educational level remains a strong
predictor for intermediate variables, with more influence on parental
support and online experience (years online), which becomes a stronger
predictor for the number of activities that children are conducting online.
Apparently the digital gap between children, based on their background,
is increasing: on the one hand, the chances that less privileged children
access the Internet earlier are decreasing, as is the range of online
activities they embrace, this results in them being less skilled and less
confident than the privileged children. On the other hand, Romanian
teenagers rely more on parental support than other children, which
provides evidence for an inter-generational transfer, which might not
always carry the best outcomes for children (fewer skills to pass on to their
children, less effective mediation, etc.).
In the Bulgarian model (χ2(16)=40.41, CFI=.974, RMSEA=0.031), as in
the case of the general model, age and child usage variables have
significant correlations with all dependent variables. Parental educational
background remains a strong predictor for the child-related variables,
thus confirming the second-level digital divide (with differences in access
and use accounting for differences in activities and skills). However,
parental usage variables have no significant influence on child’s digital
outcomes, indicating the lack of support for an inter-generational digital
transfer.
As in the case of Bulgarian adolescents, the educational background of
Hungarian parents has an indirect impact on the digital skills and
confidence of Hungarian adolescents (χ2(16)=31.72, CFI=.976,
RMSEA=0.036). However, parental usage seems to have a slight impact on
children’s digital outcomes. The case of the Hungarian digital divide is
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Closing the gap, are we there yet? 189
more a case of second-level digital divide rather than a case of intergenerational digital transfer, with differences in access and use
(determined also by socio-economical background) accounting for
differences in skills. Child-related variables (demographics and usage
being the ones that hold the most important effect), support an “emerging
differentiation” pattern of the divide.
Finally, the Polish model (χ2(16)=32.73, CFI=.978, RMSEA=0.036) shows
support for the “emerging differentiation” paradigm, for the intergenerational transfer and for the second-level digital divide. Poland was
the only case where parental usage variables had a substantial impact on
both of the children’s digital outcomes.
Discussion
The population that the EU Kids Online project surveyed was children
9–16 who use the Internet across Europe therefore the discussion around
this data has to be already situated in the framework of “second-level
digital divide.” The present chapter aimed to offer a comprehensive
explanatory framework for the patterns of digital inequalities among
adolescents (aged 11 to 16) in four CEE countries, namely Bulgaria,
Hungary, Poland and Romania. Taking into account different theoretical
approaches, we pitted several models against each other, in order to make
sense of the second-level digital divide(s) among the teenagers in our
sample. Simultaneously, we examined the plausibility of a model of
emerging differentiation, with a specific variant of the “rich get richer”
hypothesis (with differences in access and use accounting for differences
in activities, skills and confidence), of the conflict perspective (differences
in socio-economical background determining differences in activities,
skills and confidence) and finally, a model of inter-generational digital
transfer, where parental digital literacy and competence influence their
children’s own skills and confidence in Internet use.
Consistent with previous evidence, we found that older children and
those coming from households with higher educational backgrounds enjoy
better access (more private use, both at home and mobile) and longer use
(more years online, longer time spent online). Gender did not hold a
particularly strong effect, although, as in previous findings, boys tend, to
some degree, to use the Internet longer (for more years, also more
throughout a day) or to develop more confidence in using the Internet.
Due to the connection between educational background and domestication
of digital technologies (Bonfadelli, 2002; Korupp and Szydlik, 2005), we
expected a connection between parental education and children’s Internet
use. In all four cases, the socio-economical background (here, the
education of the household) held significant influences on children’s
digital outcomes (competencies, confidence). As we found, Internet
inequalities are mapped into existing inequalities and further amplify
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190 Monica Barbovschi and Bianca Fizeşan
these inequalities in some cases, indicating support for the conflict
paradigm (Witte and Mannon, 2010).
The data from all countries demonstrated child-specific
differentiations, with variables of background and usage having a strong
impact on the digital outcomes, offering support for the emerging
differentiation model and the “rich get richer” paradigm (years online for
Romania and Bulgaria, and private use for Poland and Hungary).
Finally, the model of inter-generational digital transfer was moderately
supported only for Romanian and Polish teenagers.
In terms of policy recommendations, Romanian and Polish children
could benefit more from the opportunities the Internet has to offer if
given stronger parental guidance and support. As long as the parents
remain digitally illiterate, there is little they can offer to their children in
order to ensure the maximization of “digital benefits.” In addition, the
strong link between children’s usage, activities, competencies and
confidence in own Internet skills, evidenced also by Hasebrink et al. (2011),
indicates that policy interventions (from politicians, teachers, educational
providers, industry, e-safety networks, etc.) should be directed towards
developing more digital competencies in children and teenagers, thus
creating a “virtuous circle” (more competencies, resulting in more
activities, leading to more confidence, allowing more opportunities).
Finally, as confirmed by previous studies (Livingstone and Helsper, 2010),
increasing quality of access (more private use, more points of access)
would contribute to closing the gap between the level of Internet
opportunities accessed by children. We are not there yet, but hopefully we
are slowly getting closer.
The limitations of our analyses touch different levels, two of them being
more salient for the scope and purpose of this book. First, the data
collected in the EU Kids Online project allows analyses mostly at a level of
second-level digital divide, since the survey population was children aged
9–16 who use the Internet. Another limitation sprang from our theoretical
framework: although we tried to compare different theoretical models,
deciding a priori which theories to include is an intrinsic flaw of
“quantitative sociological thinking.” For example, our model did not
include variables related to the mediation of children’s Internet use by
peers or teachers. In spite of these, we hope that our chapter has offered a
substantial contribution in providing a nuanced understanding of the
digital differences among teenagers in CEE countries. Much remains to be
explored and constantly updated due to the changing nature of the digital
landscape.
References
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empirical investigation. European Journal of Communication, 17, 65–84.
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Closing the gap, are we there yet? 191
DiMaggio, P. (2001). Social implications of the Internet. Annual Review of Sociology,
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DiMaggio, P., Hargittai, E., Celeste, C. and Shafer, S. (2004). Digital Inequality: From
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Hargittai, E. (2002). Second-level digital divide: Differences in people’s online
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Hargittai, E. and Hinnant, A. (2008). Digital inequality: Differences in young
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Hargittai, E. and Zillien, N. (2009). Digital distinction: Status-specific types of
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Hasebrink, U., Görzig, A., Haddon, L., Kalmus, V. and Livingstone, S. (2011).
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Howard, P., Rainie, L. and Jones, S. (2001). Days and nights on the Internet: The
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Kline, R. B. (2005). Principles and practice of structural equation modeling, 2nd Edition.
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Korupp, S. E. and Szydlik, M. (2005). Causes and trends of the digital divide.
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Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V. and Crawford, A.
(2002). Internet paradox revisited. Journal of Social Issues, 58, 49–74.
Livingstone, S. and Helsper, E. (2007). Gradations in digital inclusion: Children,
young people and the digital divide. New Media & Society, 9, 671–696.
Livingstone, S. and Helsper, E. (2010). Balancing opportunities and risks in
teenagers’ use of the Internet: The role of online skills and family context. New
Media and Society,12(2), 309–329.
Livingstone, S., Bober, M. and Helsper, E. (2005). Internet literacy among children and
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Livingstone, S., Haddon, L., Görzig, A. and Ólafsson, K. (2011). Risks and safety on the
Internet: The perspective of European children. Full findings. London: EU Kids Online.
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McKenna, K. Y. A., Green, A. S. and Gleason, M. E. J. (2002). Relationship
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Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet
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Oliver, M. and Shapiro, T. M. (1995). Black wealth/white wealth: A new perspective on
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“disappearing digital divide” versus the “emerging digital differentiation”
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Selwyn, N. (2004). Technology and social inclusion. British Journal of Educational
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Van Dijk, J. (1999). The network society: Social aspects of new media. London: Sage.
Van Dijk, J. (2005). The deepening divide. London: Sage.
Van Dijk, J. and Hacker, K. (2003). The digital divide as a complex and dynamic
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Notes
1 This chapter is based on the data collected by the EU Kids Online II project,
funded by the EC Safer Internet Programme, http://ec.europa.eu/information_
society/activities/sip/ from 2009–2011 (contract SIP-KEP-321803). For detailed
reports, consult www.eukidsonline.net.
2 DiMaggio and Hargittai name capital-enhancing activities as those activities
that may lead to more informed political participation, help with one’s career
advancement, or consultation of information about financial and health
services. They argue that not all online activities are equally important to
enhancing one’s human, financial, and social capital (Hargittai and Hinnant,
2008; DiMaggio et al., 2004).
3 These are resources linked to different kinds of access to digital technology
that van Dijk (2005: 20) discusses: temporal resources, material resources,
mental resources, social resources, and cultural resources.
4 All VIF and toleration coefficients were at acceptable levels.
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12 Behind the slogan
of “e-State”
Digital stratification in Estonia1
Veronika Kalmus
Kairi Talves
Pille Pruulmann-Vengerfeldt
University of Tartu
Introduction
The post-socialist transition in Estonia is often viewed as a particular case
among Central and East European countries. Specifically, the economic
reforms in Estonia have been most radical, particularly with regard to
highly liberal transformation policies, sometimes highlighted as the key
component of the success of the Estonian case. Moreover, societal changes
mixed with political aspirations and radical reforms enjoyed high
legitimacy, largely due to the still-perceived “Russian threat” and narratives
about the first period of independence (1918–1940) as the “good old days”
(Vihalemm and Kalmus, 2009), enabling the presentation of the transition
as a “return to Europe” or even as a “return to normality” (Helemäe and
Saar, 2011). However, Lauristin and Vihalemm (2009) emphasize that the
economy-centered transition culture has taken the perspectives of the most
successful social actors and framed these as self-evident aims for the whole
society, thus legitimizing the political approaches that prioritize the
economic dimensions of the reform and devalue their social implications.
Closely related to the economy-dominated paradigm, technological
change has also been a crucial component of Estonian transition.
“Internetization” has become one of the central symbols of the rapidly
changing society, leading to a widely held perception of Estonia as a
leading e-state (Runnel et al., 2009).
Witte and Mannon stress the need for understanding “how the Internet
is mapped onto existing social inequalities” and “the ways in which digital
technology feeds off the social context wherein inequality plays a starring
role” (Witte and Mannon, 2010, p. 51). In this chapter, we aim to analyze
digital stratification in Estonia with the focus on different aspects of access
to and use of the Internet. We place our analysis in the context of social
stratification in Estonia to see whether the hopes prevailing in the
information society policies about ICTs closing the gaps between different
social groups can be confirmed.
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194 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
Partially due to the 50-year-long Soviet regime, which almost totally
eradicated class-based social differentiation, the class structure in Estonia
is vague, unsettled and blended with different markers of social status.
Therefore, our starting point for exploring (digital) stratification in
Estonia is a cultural perspective, which turns “attention to the multidimensional nature of inequality” and “raises the issue of lifestyle and
consumption, which become critical angles to evaluate the impact of new
forms of information and communication technology” (Witte and
Mannon, 2010, p. 86).
Stratification in Estonia
Max Weber has drawn a distinction between “class” and “status”, arguing
that classes are groups of people who, from the standpoint of specific
interests, have the same economic position. Positively and negatively
privileged status groups are formed on the basis of claiming social esteem
or lack of it, which is typically practiced as well as expressed through a
specific style of life. Status may rest on class position; however, it is not
solely determined by it. Money and entrepreneurial position are not in
themselves status qualifications, although they may lead to them, and the
lack of property is not in itself a status disqualification, although this may
be a reason for it (Weber, 1978 [1922], p. 306).
Similarly, Pierre Bourdieu accepts economic capital as the main
principle of domination in capitalist society, but observes that the efficacy
of economic capital as a principle of stratification is constantly challenged
by fractions of the dominant class (e.g. artists, professionals and
academics) who are relatively poor in economic capital, but who by nature
of their social role, are rich in cultural and/or other forms of capital,
striving to enhance their specific form of capital as a rivaling principle.
Bourdieu, thus, extends the concept of capital with multiple forms of
capitals, which are increasingly becoming a new basis of social
stratification. He argues that members of the class share the same
objective structures, which give them the same objective meanings of
collective practices. These common practices include similarities in
lifestyle or certain “taste” that is reflected in “habitus” (Bourdieu, 1984
[1979], p. 311). In contemporary societies where ICTs are becoming
increasingly important in almost all spheres of life, differences in capitals,
taste, and habitus manifest more and more in distinctive consumption
patterns, self-expression, and cultural practices that are based upon
unequal access to ICT products and digital services.
Patterns of social and digital stratification in Estonia need to be seen
in the context of yet unsettled and somewhat paradoxical differentiation
of classes and status groups, resulting from rapid changes in the political
and economic order in the past century. After the collapse of the Soviet
Union in 1991, emerging stratification manifested in significant income
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Behind the slogan of “e-State” 195
differences. Processes of privatization and liberalization of the market
resulted in a remarkable gap between different classes with regard to
quantitative (e.g. Gini index) and qualitative (e.g. lack of social
coherence) measures. Emerging economic inequality led to a discourse
about “two Estonias” where the “winners” of the transformation enjoyed
the benefits of the growing economy and the “losers” were lagging
behind (Lauristin, 2003). Additionally, such division clearly reflected the
mind-set and value system of the society, which highlighted economic
means as the measure of success and emphasized individuals’
responsibility in social mobility.
Although stratification is still largely explained by the economic aspect,
studies have indicated the diversification of stratification and emergence
of the gaps between class-based and status-based social esteem (Lindeman,
2011). Perceived social status is more clearly shaped not just by labor
market success as measured by income, but is also dependent on
demographic predictors such as age, gender, and ethnicity. Increased risks
and vulnerability to transformation were shifted towards more
disadvantaged social groups. For example, it is argued that Estonia
experienced a change from a “gerontocratic” to a “youth-oriented” society
(Tallo and Terk, 1998). Studies of perceived social status (e.g. Lindeman,
2011) indeed have shown significant differences from Western countries
with Estonian young people estimating their social position to be higher,
compared to other age groups, regardless of education and income. The
oldest age group that mostly includes pensioners has the lowest perceived
social status. Such differences may seem surprising, taking account of the
fact that the youth unemployment rate in Estonia is one of the highest in
Europe. The paradox can be explained by considering that status-based
stratification is related to lifestyle and social practices. Studies of
consumption and media use in Estonia (Lauristin, 2004) demonstrated
that perceived social status was strongly influenced by the level of
adaptation to the standards of the emerging consumer and information
society. Consumerist orientation and digital skills as new success markers
were most rapidly adopted by younger generations, while more inert
elderly people experienced a decline in social status and even
marginalization.
Status-based stratification is also influenced by complex and multidimensional inequalities between men and women. On the one hand,
women have, on average, higher education levels than men, and they
enjoy equal participation in jobs. On the other hand, gender segregation
on the labor market, a high gender pay gap, and unbalanced gender
roles in the domestic sphere (Vainu et al., 2010) are still marking the
reproduction of traditional patriarchal structures and gender
stereotypes in the society.
After 1991, Russians and other ethnic minorities faced a double
challenge of self-determination: in terms of post-socialist transition and
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196 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
the restored Estonian nation-state (Vihalemm and Kalmus, 2009). The
new situation set the Russian-speaking community into a marginalized
position, characterized by objective indicators such as higher
unemployment rates and job insecurity, as well as subjective feelings of
inequality and exclusion, and non-activism in politics.
Education and employment status are also important resources for
sensing oneself higher in the social hierarchy. Compared to people with
higher levels of education, those with lower levels of education are more
likely to give a lower estimation of their social status. People who are
employed are more likely to estimate their social position significantly
higher than the unemployed or retired people, even when income is
controlled for (Lindeman, 2011).
To sum up, the most privileged group in Estonia regarding both the
class and status characteristics is young, employed ethnic Estonians with
high education and income levels (Lindeman, 2011). In the following
analysis, we explore whether this pattern also holds with regard to digital
stratification.
From digital divide to digital stratification
The term “digital divide” was coined to indicate the gap between “haves”
and “have-nots,” resulting directly from lack of access or related skills to
use ICTs in order to maximally gain in terms of information, various types
of capital, and other socially desirable benefits. Lack of access will result in
“digibetism” (that is, lack of digital literacy), which in turn will lead to
societies divided between the information rich and the information poor
(Carpentier, 2003).
Access-related questions dominated in digital divide research in the
1990s. In the next decade, the focus shifted to more diverse and rich
descriptions of various shades of inequalities related to the new
information and communication technologies. For example, Jan van Dijk
(2006) has drawn attention to skills, knowledge, and motivation as
important aspects of creating digital stratification. Furthermore, the
digital divides are no longer seen as a problem of an individual but rather
as resulting from contextual and social resources (Tsatsou et al., 2009).
Deepening digital divides, in turn, reproduce and aggravate social
stratification, thus effectively hindering information society developments,
especially in the context where both public and private sphere services are
increasingly becoming available exclusively online. Hence, the digital
divides are both seen as a symptom and a cause of broader economic
inequality and social exclusion (Parayil, 2005).
In proceeding to analyze digital stratification in Estonia from the
cultural perspective, we view digital inequality as multi-dimensional, that
is, as being related to class position and status differences (Witte and
Mannon, 2010). On top of that, we assume that differences in Internet use
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Behind the slogan of “e-State” 197
are conditioned by a number of other factors such as individuals’ lifespan,
their social roles and duties, and social capital and integration in the
society. These factors vary greatly depending on demographic
characteristics that are, together with indicators of social class and status,
the focus of our chapter.
Our analysis is based on data from the third wave of the survey Me. The
World. The Media, conducted in October 2008. The survey covered the
Estonian population aged 15 to 74 years, with a total sample size of 1,507
respondents. A proportional model of the general population (by areas
and urban/rural division) and multi-step probability random sampling
(realized through primary random sampling of settlements with a
proportional likelihood related to the size of the settlement, followed by
random sampling of households and individuals) was used. In addition, a
quota was applied to include a proportional number of representatives of
the ethnic majority and the minority, differentiated according to the
preferred language of the survey interview (Estonian or Russian,
respectively). A face-to-face interviewing method was used.
In our analysis, we employ three demographic characteristics: gender,
age, and ethnicity. For the latter, we use the preferred language of the
survey interview (Estonian for the ethnic majority, and Russian for the
minority). In addition, we make use of two indicators of social class – level
of education and income per family member – and an indicator of social
status. The latter was conceptualized in the study as social representation
of stratification, and operationalized as respondents’ self-evaluated
position on the imagined social ladder, visually presented in the
questionnaire in the form of a stairway, rising from step one to step ten (cf.
Lauristin, 2004). The resulting variable was shortened to a five-point scale,
ranging from 1 – low stratum to 5 – high stratum. This indicator of social
status, approximating to normal distribution, was not dependent on
gender. Ethnic Estonians estimated their status somewhat higher (M =
3.25; SD = 1.30) than the Russian-speaking minority did (M = 3.09; SD =
1.33; p < 0.05). As expected, perceived social status was negatively
correlated with age (r = –.25; p < 0.001). Furthermore, status was positively
correlated with the number of years in education (r = 0.24; p < 0.001), but
even more strongly with income per family member (r = 0.33; p < 0.001).
This suggests that in Estonia, as a transition society, economic success still
tends to dominate over educational and cultural factors in the formation
of social representation of stratification, confirming the findings of the
first wave of the Me. The World. The Media survey in 2002 (Lauristin,
2004).
To find out patterns of digital inequality, we first introduce a basic
division of Internet users and non-users. Altogether 73 percent of the
respondents were Internet users at the time of the survey. Figure 12.1 shows
statistically significant differences based on language, age, education,
income and social status. Thus, the divides in access and basic usage of the
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198 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
14
28 36
38
15
7
61
70
70 74 75 67
97 96 69
76
63 71
58
86
72
64 62
85 93
39
Age**
more than 10000 EEK
4001-6000 EEK
6001-10000 EEK
2501-4000 EEK
Higher
up to 2500 EEK
Secondary
60-74
Primary
50-59
40-49
30-39
20-29
15-19
Russian
Estonian
Male
Female
30
Gender Language
of the
survey**
40
Education, income per
family member**
60
9
25 18
91
75 82
High stratum
37 29
42
Medium stratum
24
Do you use the Internet? No
High-medium stratum
4 11
Low stratum
30 26 25 33
3
Lower-medium stratum
Do you use the Internet? Yes
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Social status**
Figure 12.1 Internet users and non-users in Estonia (N = 1,507).
Note: ** p < 0.01.
Internet mirror quite adequately the patterns of social stratification
described above. Compared to the results of the 2002 survey data (Runnel
and Pruulmann-Vengerfeldt, 2004), according to which significantly more
men were using the Internet, we can say that the gender gap in access has
closed. The divides based on language, age and education have remained
the same. The relationship with income was linear in 2002 with fewer
Internet users among the low-income groups but showed a non-linear
curve in 2008 with somewhat more Internet users in the two lower and the
two higher income groups compared to the middle-income group. This
may be explained by the fact that families with children tend to have lower
income per family member, while being avid Internet users.
Inequalities in Internet use
In the following analysis we focus on socio-demographic differences in the
intensity and versatility of Internet use. We employ the sub-sample of
Internet users of the 2008 wave of the Me. The World. The Media survey.
As 369 respondents answered that they had never used the Internet, and
38 respondents did not answer the question, 1,100 participants remained
in this analysis with mean age of 38.29 years (SD = 14.76). Of the remaining
sample, 55 percent were females; 70 percent of the respondents completed
the questionnaire in Estonian and 30 percent in Russian, respectively.
For the indicator of the intensity of Internet use we employ an index of
the frequency of Internet use, measured with three items: How frequently
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Behind the slogan of “e-State” 199
do you use the Internet (1) at work or school, (2) at home, and (3)
elsewhere (Internet cafés, public Wi-Fi hotspots, at friends’ places, etc.).
The respondents were asked to answer each question on a five-point scale,
ranging from 0 – not at all to 4 – almost every day. The maximum value of
the index is, thus, 12.
To compare the versatility of Internet use, extending to different
spheres of life, we make use of an empirically robust and theoretically
easily interpretable classification of online activities, drawn upon the same
database in a previous analysis (see Kalmus et al., 2011). Based on factor
analysis of 30 online activities, the previous study proposed a simple and
stable two-factor structure. The first factor, labeled as “social media and
entertainment related Internet use” (hereafter, SME), contains variables
such as searching for and managing information regarding friends and
acquaintances on social networking portals; searching for entertainment;
participating in forums, blogs, surveys, and writing comments;
communicating with friends and acquaintances; and sharing music, films,
and programs, and is indicative of personal need for entertainment, fun,
self-expression, and maintaining social relations. The second factor,
labeled as “work and information related Internet use” (hereafter WI),
includes activities such as searching for information about public
institutions, ministries, courts, etc.; using e-services (tax board, forms,
citizens’ portal, etc.); work-related communication with clients and
colleagues; searching for practical information (weather, timetables, etc.);
within-organization communication (intranet, lists, etc.); searching for
information and tips on relationships, family, children, child-rearing,
health and other aspects of personal life, and refers to people’s motives to
use the Internet for practical and work-, role- or institution-driven
purposes. It can be suggested that these factors and, accordingly, two
underlying motives for Internet use, correspond to two aspects of an
information environment – a personal/relational aspect and an
institutional aspect – delineated by Lievrouw (2001) in her insightful
theoretical essay.
Table 12.1 presents the mean values of the index of Internet use
frequency and the mean factor scores of two factors of online activities
among gender and ethnic groups. The difference between men and
women in the intensity of Internet use was not statistically significant. An
interesting polarization between males and females, however, appeared
with regard to the types of online activities: women scored significantly
higher than men on WI, whereas men used the Internet more than women
for SME. These gender differences might be explained by the so-called
second shift (Hochschild and Machung, 1989): the gender regime, while
favoring women’s active participation in the labor market, simultaneously
associates home-making and child-rearing mostly with females. This
implicates that women have less spare time compared to men. Recent
studies indicate that this phenomenon is particularly prominent in
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200 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
Estonia: according to the 2010 Time Use Survey, women, on top of their
daily paid labor, spend on average 4.1 hours a day on household duties,
compared to men’s 2.6 hours. At the same time, women have on average
5.3 hours a day as leisure time, while men have 6.1 hours (Tasuja, 2011).
Thus, the overwhelming importance of institutional duties, including
gendered role division in families, probably motivates women to use their
time online for practical and work-related purposes, while hindering them
from pursuing those motives for Internet use that are related to their
agency and personal needs. Similar explanations to gender inequalities in
Internet use have also been proposed by other authors (e.g. Hargittai and
Shafer, 2006; Dutton et al., 2009).
The difference between the ethnic majority and the minority with
regard to Internet use frequency was not significant (Table 12.1). Those
who completed the questionnaire in Estonian used the Internet
significantly more for WI, that is, the institutional aspect of the
information environment, than those who responded to the survey in
Russian. Members of the ethnic minority, however, scored significantly
higher on more personal uses of the Internet (SME) than Estonianspeakers did. These findings may be indicative of a weaker vertical
integration of the minority group in the Estonian society, that is, their
looser ties with state institutions (Ehin, 2009), and lower use of national
online and offline news media (Vihalemm, 2008). Still, the findings
point at the potential for horizontal integration of the ethnic minorities
through social networking sites (SNS) and interpersonal online
communication.
Table 12.2 displays Pearson’s correlations between the characteristics of
Internet use, age and indicators of social class and status. Age was strongly
Table 12.1 Characteristics of Internet use by gender and language (N = 1,100)
Frequency of Internet
use
Work and information Social media and
related Internet use (WI) entertainment related
Internet use (SME)
Mean
SD
Mean
SD
Mean
SD
Males
Females
6.32
6.02
2.97
2.90
–0.15**
0.12**
0.98
1.00
0.13**
–0.10**
1.01
0.98
Estonian
speakers
6.26
2.89
0.09**
1.01
–0.04*
0.99
Russian
speakers
5.91
3.02
–0.22**
0.94
0.10*
1.02
Note: * p < 0.05; ** p < 0.001.
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Behind the slogan of “e-State” 201
Table 12.2 Correlations between the characteristics of Internet use, age and
indicators of social class and status
Frequency of
Internet use
Age
–0.41***
Work and
information
related Internet use
(WI)
Social media and
entertainment
related Internet use
(SME)
0.01
–0.62***
Education (in years)
0.16***
0.36***
–0.19***
Income
0.17***
0.17***
–0.09**
Perceived social status
0.28***
0.19***
0.08*
Note: * p < 0.05; ** p < 0.01; *** p < 0.001.
and negatively correlated with the frequency of Internet use and SME,
while the correlation between age and WI was near zero.
Figure 12.2 shows the mean levels of the two types of Internet use in age
and gender groups. WI trajectory across the lifespan is better described as
curvilinear, with this motive for Internet use being relatively low among
the youngest and the oldest age group, and reaching its highest level
around 30 to 44 years of age. This suggests that the importance of the
institutional aspect of an information environment is related to one’s
lifespan and social roles, implicating that older age groups are still more
deprived of the opportunity of interacting with societal institutions via
new media.
SME was highest among the youngest age group, decreasing steadily
throughout the lifespan. Our results, in line with the findings of other
studies (e.g. Dutton et al., 2009), thus, suggest that young people’s motives
for using the Internet indeed largely derive from their agency, free will,
and interest in interactive opportunities offered by the new media.
Interestingly, differences between males and females are non-existent
among 15 to 19 year olds, and become particularly notable between the
ages of 30 and 54. These dynamics of gender differences lend support to
the above-proposed explanation that the double workload, most acute at
the age of parenting, leads women to use their time online for practical
and work-related purposes, while limiting entertainment-oriented uses.
The intensity of Internet use was significantly positively correlated with
the indicators of social class, that is, education and income, as well as with
perceived social status (Table 12.2). Similarly, correlations between WI
and all three indicators of social class and status turned out to be positive,
being especially strong with regard to the level of education. Interestingly,
the indicators of social class were negatively correlated with the personal
aspect of Internet use (SME), while perceived social status, on the contrary,
turned out to be weakly, but still significantly, positively correlated with
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202 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
1.5
1
WI All
0.5
WI Males
WI Females
0
SME All
SME Males
-0.5
SME Females
-1
-1.5
15-19
20-29
30-44
45-54
55-64
65-74
Figure 12.2 The motives for Internet use in age and gender groups (N = 989).
Note: The difference between age groups in WI and SME scores was statistically significant
in the whole sample and among both gender groups at p < 0.001.
SME. These correlation patterns demonstrate, in line with the cultural
perspective presented in Witte and Mannon (2010), that the association
between Internet use and social status is independent of the effects of class
differences. It is possible that better-off and, in particular, better-educated
users are driven by pragmatic motivation as they might benefit from WI
related activities much more compared to SME related use in their pursuit
to maintain the position of advantage (cf. Zillien and Hargittai, 2009).
Accordingly, they may prioritize work and information related activities over
more entertainment-oriented uses in allocating their scarce time resources.
Scoring higher on both types of online activities as well as on the overall
intensity of Internet use seems to be, somewhat differently, the function of
higher social status and the corresponding values, habitus and lifestyle.
To find out to what extent the three characteristics of Internet use are
predicted by demographic variables versus the indicators of social class
and status we conducted a series of linear regression analyses (Table 12.3).
Starting from the intensity of Internet use we can observe that younger age
was the strongest predictor of Internet use frequency, followed by higher
education levels, status and income. The ethnic majority status was a weak
but significant predictor in the two regression models. Altogether, the
indicators of social class and status increased the explained variance by 12
percent.
Due to the curvilinear relationship between WI and age, the agesquared variable was added to the regression models predicting work and
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Behind the slogan of “e-State” 203
information related Internet use. Higher education levels turned out to be
the strongest predictor of WI, with the ethnic majority status, being a
female, higher social status, higher income and the age variables all
significantly contributing to predicting this type of Internet use. Similarly,
to the case of Internet use frequency, adding the indicators of social class
and status considerably enhanced the model, increasing the explained
variance by 13 percent.
Finally, SME was, by far, most strongly predicted by younger, followed by
being a male, lower level of education, higher social status and, in one of
the models, weakly but significantly by the ethnic minority status.
Differently from the cases of Internet use frequency and WI, adding the
indicators of social class and status did not enhance the model remarkably,
suggesting that the more personal and agency-related aspect of Internet
use is, predominantly, the function of inter-generational differences.
From our analytical perspective, it is important to note that perceived
social status was the only variable that was significantly positively
correlated with all aspects of Internet use, that is, with the intensive as well
as extensive nature of online activities. This can be seen as a particularity
Table 12.3 Linear regression analysis exploring how demographic variables and
indicators of social class and status predict the characteristics of Internet use
Frequency of Internet
use
Work and information
related Internet use
(WI)
Social media and
entertainment related
Internet use (SME)
Model 1
Model 2
Model 1
Model 2
Model 1
Model 2
Gender
0.03
0.01
–0.12***
–0.11***
0.09***
0.08**
Language
0.07*
0.07*
0.15***
0.16***
–0.04
–0.05*
–0.41***
–0.45***
1.34***
0.90***
–0.61***
–0.60***
Age
squared
—
—
–1.36***
–0.98***
—
—
Education
(in years)
—
0.19***
—
0.32***
—
–0.08**
Income
—
0.12***
—
0.07*
—
–0.01
Perceived
social
status
—
0.17***
—
0.09**
—
0.06*
0.39
0.41
Age
R2
0.17
0.29
0.10
0.23
Notes:
Language of the survey (1 = Estonian; 0 = Russian); gender (1 = male; 0 = female).
* p < 0.05; ** p < 0.01; *** p < 0.001.
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204 Veronica Kalmus, Kairi Talves and Pille Pruulmann-Vengerfeldt
of a rapidly informatizing transition society where higher perceived social
status not only fosters and urges individuals to advance the intensity and
scope of their online activities, but is also influenced by successful and
swift adaptation to social and technological changes (cf. Lauristin, 2004).
Conclusions
Our analysis indicated that the socio-demographic differences in access to
and use of the Internet largely correspond to the patterns of social
stratification in Estonia. With regard to access and use frequency, more
advantaged social groups (younger generations, well-educated and welloff people, those with higher social status, and, to some extent, the ethnic
majority) have maintained their lead in adaptation to social transition. In
terms of Internet uses, a clear differentiation has emerged, with females,
the ethnic majority, middle-aged people, and better-educated and betteroff people leaning towards the institutional aspect of an information
environment, and males, the ethnic minority, the youngest generations,
and people with lower education levels and income preferring the
personal/relational uses. Somewhat differently from American society
where the well-off and well-educated succeeded in the intensive as well as
extensive nature of Internet use (Witte and Mannon, 2010), social status
rather than social class predicted both the intensity and versatility of
Internet use in Estonia. We may conclude that in a rapidly changing
society where the class structure is still unsettled, a set of different
resources such as economic and cultural capital, digital literacy and
sufficient leisure time are needed to flourish in all aspects of the emerging
information society, which, in turn, contributes to advancing one’s capitals
and the perceived social status.
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Note
1 The writing of this chapter was supported by grants from the Estonian
Research Agency (ETF8527 and SF0180017s07).
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Section 5
The Middle East region
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13 Digitally divided we stand
The contribution of digital
media to the Arab Spring
David M. Faris
Roosevelt University
Introduction
On a bright summer night in July 2011, Egyptian digital activists gathered
in Tahrir Square to discuss police abuse and torture, and ongoing failure
of the military regime that succeeded Hosni Mubarak to reform the
country’s corrupt Ministry of Interior. The “Twitterati,” as these elite,
Cairo-based activists were derisively known, were not sitting alone in their
apartments tweeting, texting and posting on Facebook, but rather engaged
in an attempt to include their non-wired citizens in a dialogue about
important national issues. Two or three hundred Egyptians sat in solidarity
at the far edge of the square, with the burned-out husk of the recentlydeposed National Democratic Party headquarters in the background, and
communicated not just with the microphone but also with the non-verbal
hand-signals that would become famous in the United States when
employed later that summer by Occupy Wall Street protestors. These
events had become known as “Tweet Nadwas” – hash-tagged, ad-hoc
conferences about the significant challenges facing the Egyptian
revolution and the dangers of losing the energy and exuberance of Tahrir
Square to the forces of what had become known as the “counterrevolution.” Sitting in the crowd were the familiar faces of Egypt’s decadelong digital counter-public, but also a cross-section of less privileged
Egyptians, who were sharing the square in an attempt to realize justice for
the revolution’s “martyrs” – those who lost their lives in Cairo, Suez and
other parts of Egypt during the 18 days of the uprising in January and
February of 2011 against one of the longest-tenured authoritarian regimes
in the world.
The well-known role of digital activists in the Egyptian uprising in
particular, and the Arab Spring in general, raises important questions
about digital access and fluency in the developing world, and about the
relationship between elites and non-elites on the Internet. Egypt is both a
relatively poor and unequal society, with the benefits of Mubarak-era
neoliberal reforms distributed quite unevenly. On the one hand, largely
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210 David M. Faris
urban business elites and upper middle class Egyptians have captured the
very real growth of the past 20 years, and are connected to global capital
flows and trends. It is these groups who have seen their access to
broadband Internet and wireless networks grow substantially since the
turn of the century, while digital infrastructure in the rest of the country
lags seriously behind. Is Egypt’s (and the region’s) digital divide merely
reinforcing extant social inequalities, or are digital tools increasing access
to information and economic opportunities for regional citizens who
might otherwise be left behind? These important questions will be
examined through the lens of classic sociological theories about inequality
and class.
The digital divide and social science traditions
In Witte and Mannon’s The Internet and Social Inequalities (2010), the
authors analyze the “digital divide” through the lens of three major
sociological traditions: the material, cultural and functional
perspectives. For the functionalist perspective, Witte and Mannon ask,
“Does it matter that many individuals do not use the Internet on a daily
basis if, in the end, society benefits from information and innovations
provided by the Internet?” Functionalism in fact became one of the
defining foundations of contemporary political science (Sil, 2000,
p. 355), as “modernization theory” – the idea that through increasing
specialization, urbanization, and technological advancement, all
societies were on a common trajectory from traditional to modern. The
explosion of Internet penetration into less developed countries would fit
squarely into the tradition’s focus on the number of telephone lines and
television sets as proxies for the “modern.” While the materialist
tradition would decry the inequalities wrought by and reinforced by the
unequal spread of digital technologies, the functionalist paradigm
would see in them merely a reaffirmation of the division of labor. Not
everyone can be an expert in digital technologies, nor each individual an
activist. And society as a whole might benefit from their efforts, even if
they do not quite share in them equally. For Durkheim, the division of
labor allows the “cohesion of societies,” and thus “must possess a moral
character” (Durkheim, 1984, pp. 23–24). Therefore, while allowing that
the benefits of digital technologies have been unequally shared, in both
the developed and developing worlds, can we make a case for their
essential utility for social solidarity and cohesion?
Without offering an unconditional “no” to this question, this essay will
adopt the functionalist perspective for analyzing the broad contributions
of the Internet to societies in the Middle East. In other words, even while
acknowledging the unequal impact of digital tools on different social
classes in countries like Egypt and Tunisia (Fahmy and Rifaat, 2010)
(which do matter, of course), I will argue that the Internet has brought
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Digitally divided we stand 211
benefits that both justify some of the optimism surrounding these
technologies, and offer hope that some of those benefits might ultimately
redound to the benefit of less privileged classes and groups. Insofar as
they have contributed to a political shake-up across the region, that
promises to empower citizens to make political and economic choices
about their own lives, rather than submitting to the whims of authoritarian
rulers, digital inequalities can be at least temporarily justified.
The spread of the Internet has been beneficial for the Middle East in a
multitude of ways. First, there are, in fact, many ways that visitors to the
region can see some of the benefits brought by the increasing penetration
of broadband access. From e-government initiatives that put crucial
information for citizens online, to the proliferation of food-ordering Web
sites that connect individuals with food vendors that they might not have
ordinarily encountered nor had immediate access to, the Internet has
almost certainly contributed to both economic growth and general
transparency. In Cairo, for instance, you can now order food from nearly
any restaurant in the city through a site called Otlob and have it delivered
to your doorstep. Restaurants whose markets might once have barely
extended beyond a three-block radius can now count half of sprawling
Cairo as their customer bases. Anyone who has actually been to Cairo and
tried to decipher its labyrinthine street grid should understand what an
accomplishment this truly is. And while reaping the economic gains of
these innovations is more difficult the further down the economic food
chain you move, it is also true that even working class Egyptians might
make occasional use of such services through Internet cafes or the
common broadband connections in apartment buildings. This is a clear
example of a broad social benefit that can be justified morally despite the
fact that its benefits are not shared equally.
States in the Middle East have long posed increased access to
information technology as one of the keys to building more prosperous
global economies. In 1999, the government of Hosni Mubarak unveiled a
major initiative to enhance Egypt’s digital infrastructure, forming a
cabinet ministry called the Ministry of Communication and Information
Technology (Wheeler, 2003, p. 631). That initiative has paid dividends, as
rates of Internet access have risen rapidly in the past ten years, a pattern
that has been clear across the region, as governments scrambled to catch
up to other countries. Countries are also scrambling to claim a share of
the market for digital platforms and applications. In fact, while rates of
access have started to level off in many parts of the world, the Middle East
is still witnessing explosive growth due to its initial lag in widespread
adoption of the technologies. It is not just broadband – across the region
digital mobile networks have grown at astonishing rates, and many
individuals who can afford to do so now access the Internet primarily
through their mobile phones. This has, of course, only reinforced the
divide between elites with the income to spend on such devices, and the
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212 David M. Faris
masses, who still access the Internet communally, sporadically in Internet
cafes, or through poor-performing home access points.
But the Middle East is not an ordinary region – as of December 2010, it
was characterized by pervasive authoritarianism, and had seemed to
completely avoid the movement toward electoral democracy witnessed in
East Asia, Latin American and Africa during the 1980s, 1990s, and 2000s
(Bellin, 2004; Posusney, 2004). Regimes had, in fact, seemingly mastered
techniques of controlled openings and liberalization for the purpose of
self-preservation rather than democratization. Prior to the uprising in
Tunisia that swept away longtime dictator Zine El-Abadine Ben Ali, the
region was characterized with few exceptions by countries with robust
repressive apparatuses, minimal civil and political rights, and economies
distorted in various ways by bloated bureaucracies, kleptocratic ruling
families, and domination by small cliques of financiers and in some cases,
military elites who captured most of the rents from liberalization for
themselves and a small coterie of clients. Media environments were
dominated more or less extensively by state-owned or state-affiliated
newspapers, television stations and radio outlets, with only satellite TV
stations like Al-Jazeera and Al-Arabiyya relieving the tedium, and even
then, both stations were owned and operated out of states that were among
the most regressive in the region. The Internet, beginning around the
turn of this century, offered dissidents in nearly all of the authoritarian
countries of the region, an alternate platform for expressing and
organizing dissent. The question for our purposes, is whether the use of
the Internet as an alternate public sphere and organizing platform
reinforced existing gender, religious and class hierarchies, or whether it in
some way subverted them. As I will argue below, it is clear in the cases of
Egypt and Tunisia that the digital divide is the result, rather than the
cause of, social inequalities, and that activists have used the medium to
pursue a clear set of social and political goals from which no one can be
reasonably excluded.
The digital divide and the Middle East
The term “digital divide” was used by Pippa Norris (2002) to describe
disparities in access to the Internet across social classes worldwide. Early
boosters of the Internet believed that digital tools might mitigate extant
social inequalities by providing marginalized groups with access to
information and tools of organization that might bypass barriers created
by social class. Norris argued, on the other hand, that the Internet “reflects
and thereby reinforces” political realities and social inequalities, instead of
undermining or changing them (Norris, 2002). Norris’s book was a useful
corrective to more optimistic accounts of the Internet and social change,
and sparked a debate about the potentialities of digital tools and ways to
increase access and equality on the Internet. Arguments based on Norris’s
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Digitally divided we stand 213
concept of the digital divide have in fact been quite prominent in general
skepticism about the Internet’s potential to transform developing societies,
and as such are particularly relevant to discussions of the Internet in the
Middle East.
The most recent data suggests that region-wide, women constitute only
one-third of all Facebook users, a finding that respondents attribute to
general regional cultural constraints (Arab Social Media Report, 2012).
This finding tracks generally with the lower general levels of female
literacy across the region, and thus it is not surprising to find this divide
recapitulated in the digital realm. Despite these constraints, however,
women have played a significant role in the digital dissent that has swept
the region over the past ten years, and a number of young Arab women
played prominent roles in national dramas beginning in December 2010.
Radsch argues that Arab women were relatively equal participants in
blogging (though equal participation does not of course mean equal
influence), but clearly the gender divide in digital access has prevented
such equality from reaching the more recently-developed social media
sphere (Radsch, 2012, p. 7). Etling, Faris and Palfrey, on the other hand,
found that only 34 percent of Arab blogs were written by women (2009,
p. 36). Women who have become successful activists, though, have tended
to come from the upper levels of regional class hierarchies.
Modes of inequality
The growth of broadband in places like Egypt, Yemen, and Syria slowed
throughout the 2000s, partly for economic and partly for geopolitical
reasons. In Egypt, while there were a number of vendors for broadband
service, for most of this period it remained prohibitively expensive for
average Egyptians. In cities like Cairo, the need for Internet access was
filled by two competing and stratified institutions. On the one hand, the
country witnessed the proliferation of Western-style cafes with names like
Cilantro, Joffrey’s, and Costa Coffee – in some cases these restaurants were
international ventures of companies like Coffee Bean & Tea Leaf. Stepping
off the hot, dusty streets of Cairo into one of these cafes is tantamount to
entering an alternate universe, where trendy and well-dressed Cairenes sip
expensive lattes and pick at Western-style sandwiches and paninis that cost
more than the daily salary of many other citizens. de Koning argues that
these cafes, indeed, became sites for the production and display of wealth
and status for upper middle class Cairenes (de Koning, 2006). For years
these cafes provided Internet access free of cost, but in 2008 and 2009 they
started charging for that as well, whether hourly, or by purchasing cards
with scratch-off codes that allowed for a certain time period of access. But
of course, most of the people who could afford the expensive sandwiches
and drinks in such cafes probably had Internet connections at home or
work as well.
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214 David M. Faris
At the same time, there developed another business model of Internet
cafes – places that did not serve up anything but access to the Web, and for
a small fraction of the cost of access at Cilantro. These cafes are often
located off side streets and down a set of stairs, where the proprietors usher
you to a seat and hand you a time card that keeps track of how long you
spend surfing the Internet. While this access is still pricey by the standards
of ordinary Egyptians, even working class individuals are able to afford a
few hours a week if they so desire. This is to say nothing of common
practices such as the residents of apartment buildings sharing a single
broadband connection (known as “thief nets”), or of a single mobile phone
providing the point of Internet access for multiple friends or family
members. While the official Internet penetration rate in Egypt stood at 26
percent in 2011, the actual rate of effective access might be quite a bit
higher. But it forces us to ask whether disparities in digital access time and
quality might lead to inequalities in how the Internet is harnessed for
social and economic empowerment. In other words, it is quite likely that
the elite Egyptian with unlimited broadband can do more with his or her
access than a working class Egyptian who can get online for three or four
hours a week.
Access and revolution
While general research has yet to be conducted on the demographics of
protestors during the Arab Spring more broadly, there is some data on
Internet usage and access in the Egyptian events. These access disparities
can be seen in the latest research on the Egyptian uprising, demonstrating
that it was in fact wealthier Egyptians who heard about the January 25
demonstrations on the Internet, through online social networks, and who
were overwhelmingly more likely to show up on the first day to protest.
Tufekci and Wilson’s data also show that 77 percent of the respondents who
participated in the protests had Internet at home, a rate that far eclipses that
of ordinary Egyptians (Tufekci and Wilson, 2012, p. 369). The proportion of
survey respondents who also reported using Facebook to discuss the protests
was 51 percent, as opposed to just 13 percent for Twitter (p. 370). What this
suggests is that it was precisely wealthier, more connected Egyptians who
hatched the plans for protest and executed them, but that it was only when
the non-wired citizens joined in on the protests that they were actually able
to affect large-scale change in the country. This process of elite-led diffusion
in the context of persistent social stratification reinforces the central
argument of this article, that elite digital activists enabled broad-based and
important change in spite of the digital divide.
What was the relationship between access and uprising across the
region? Diving into the data, it becomes difficult to assert any clear
relationship between rates of Internet access and the onset of revolutionary
uprisings. What seems clear is that some of the most-connected states,
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Digitally divided we stand 215
including the UAE, Saudi Arabia, and Qatar, saw minimal mobilization, or
at least mobilization that did not lead to the kind of political upheaval
witnessed in more low-connectivity states like Egypt, Libya and Syria. In
fact it is the four states with the lowest levels of Internet access in the entire
region – Egypt, Yemen, Libya, and Syria – which have so far witnessed the
most dramatic political uprisings, all of which were backed by robust
Internet-based mobilization campaigns. In the case of Egypt, the time,
date and initial mobilizing strategies were all conducted on Facebook,
making it perhaps the first mobilization that truly deserves the term
“social media revolution.” The starkness of this contrast should lead us to
conclude that something beyond simple “access” to the Internet is required
to spark dissent in authoritarian countries. Indeed, it is not access itself,
but, to borrow Witte and Mannon’s terminology, “use” of the Internet that
can best predict under what circumstances an authoritarian regime is
likely to have to contend with an uprising (2010, p. 44).
One aspect of the digital divide in the Middle East that is most salient is the
population bulge dynamics that inhere across many of the states in the region.
Many regional states have populations that are disproportionally young, from
Iran to Egypt. It is also unquestionably true that these youth populations are
much more likely than their elders not only to have Internet access, but to be
fluent in how to most efficiently use the tools at their disposal. As the Open
Net Initiative notes, “Demographic factors are also expected to contribute to
the growth of Internet population” (Open Net Initiative, 2009). Therefore
even as rates of access across the region continue to lag behind their
counterparts in Western Europe and Asia, increases in Internet access will be
captured disproportionately by the young. The salience of youth access to
digital media was highlighted during the Arab Spring, as Egyptian and
Tunisian youth activists used their preferred social media platforms to
organize the initial protests (as in Egypt) or to coordinate and amplify
ongoing protests after they had begun, as in Tunisia (Faris, 2012).
It is not just any young people, however, who are most likely to have a
dramatic impact on the politics of regional states. It is unquestionably
college-educated, middle and upper middle class youth who have seized
the mantle of digital organizing across the region. Matthew Hindman
argued that far from empowering marginalized groups in the United
States, the Internet merely transferred power to a new networked elite,
largely comprised of privileged, Ivy-League educated white men
(Hindman, 2008). Rather than leveling the playing field between different
groups and classes in American society, the Internet instead reinforced
existing class, gender, and racial hierarchies. Looking at the most popular
and influential blogs in the American “blogosphere,” Hindman concluded
that, if anything, minority representation was worse online than it was
offline. If we expect the digital divide to mirror, if not exacerbate, a
country’s general inequality, it should be no surprise that the US has a
substantial gap in this regard. Table 13.1 provides the relevant Gini
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216 David M. Faris
Table 13.1 Comparative measures for selected Middle Eastern countries
Gini Coefficient
Internet Access * %
Literacy ** %
United States
45.0
78.3
99.0
Egypt
34.4
26.4
66.4
Libya
N/A
5.9
97.7
Qatar
41.1 (2007)
66.5
N/A
Saudi Arabia
N/A
43.6
86.1
Tunisia
40.0
36.3
88.9
United Arab
Emirates
N/A
69.0
90.0
Yemen
N/A
10.8
62.4
Syria
N/A
19.8
87.9
Notes: * Source: Internet World Stats. http://www.internetworldstats.com/ (accessed May
30, 2012); ** Source: United Nations Development Program, 2011.
coefficients for the countries under consideration in this essay. The United
States is provided for comparison. Because of the relative newness of the
Gini measurements, it is impossible at present to determine whether
increased Internet access has had a measurable effect on inequality in
general.
Interestingly, the regional countries that have data available on this
question are all substantially less unequal than the United States. It should
also be noted that equality does not necessarily translate to prosperity.
While the world’s most equal country, Sweden, also happens to be quite
prosperous, very poor countries like Afghanistan and Ethiopia have lower
levels of inequality than, for instance, the EU countries as a whole (Gini
Index, 2011).
Models of dissent
What seems clear is that there is no linear relationship in the Middle East
between general levels of Internet penetration, and the use of such
technologies by dissident entrepreneurs. It is more appropriate to consider
the different models of digital activism that were deployed across the
Middle East during the Arab Spring, and to understand the ways in which
those models are influenced by architectures of state control and
surveillance. In a small number of countries like Egypt and Bahrain, state
authorities opted not to tightly filter and censor the Internet. From the
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Digitally divided we stand 217
dawn of Egyptian digital activism around the turn of the century,
dissidents found few obstacles between themselves and their ability to
create or access content on the Internet. This seemingly open road
contrasted sharply with the media environment, which even after the
liberalization of press laws in 2004, remained dominated by state TV and
state-owned or affiliated newspapers. The lack of access to traditional
channels of expression and dissent led many dissidents to use the new
tools of Web 2.0 – at the time primarily off-the-shelf blogging technology
through Blogger – as platforms for writing and thinking about ways to
challenge the state. For Egyptians, this led to a small but robust and tightlylinked network of about 1,000 activists, many based in Cairo and
Alexandria, who coordinated both with the protest movement Kefaya, and
with the new independent newspapers, to get their message out to the
broader, non-wired population. While many members of this community
were harassed, arrested, and blacklisted by traditional media
organizations, the state made little to no effort to actually block or take
down their content. In time, this allowed dissidents to build a campaign of
dissent around a small number of widely shared goals – goals that
transcended other divisions (largely between secularists and Islamists)
that have come to define post-revolutionary Egypt. Dissidents sought an
end to the Mubarak dictatorship, a lifting of the emergency law that had
governed Egypt since the 1981 assassination of President Anwar El-Sadat,
an end to practices of torture and indefinite detention, and a shifting of
Egypt’s foreign policy away from a blind subservience to US and Israeli
interests. In other words, in the open Internet environment of pre-2011
Egypt, digital activists were both thought leaders as well as coordinators of
protest (Khamis and Vaugh, 2011; Faris, 2013; Radsch, 2012; Lynch, 2012).
Likewise, while Bahrain’s uprising was ultimately crushed, its robust
blogging community is widely seen as having been at the forefront of
dissent and organizing during the 2000s (Schleusener, 2007).
Other states, however, including Syria, Tunisia, and Saudi Arabia, opted
for the “China model” of a closed Internet, governed by intrusive state
filtering and censorship. This strategy, while it successfully drove digital
activism to the margins, and forced many dissidents to do their writing
and thinking abroad, clearly gave many regimes a false sense of confidence
in their own ability to continue governing. Whereas in Egypt, dissent was
increasingly open over the past decade, in Tunisia the first inklings of
broad dissatisfaction really only became apparent in 2010, when digital
activists began holding small rallies to protest state corruption and abuse
of power. In the case of both Syria and Tunisia, the state’s decision not to
block seemingly innocuous sites like Facebook led activists to use the
group-forming and sharing capabilities of these platforms to amplify and
coordinate large-scale protests whose causes could not necessarily be
found in digital activism itself (Khamis and Vaugh, 2011). The number of
individuals involved in digital activism inside Tunisia was quite limited. As
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218 David M. Faris
the journalist and activist Afef Abrougui noted, “the number who were
active was limited, people were careful.”1 But once the floodgates of protest
had opened, Tunisians took full advantage of social media to get the word
out about protests, share images and videos of what was happening in the
streets, and to build linkages with activists outside the country. Activists
consider the contribution of these technologies to the success of the
Tunisian revolution to be quite significant. Across the region, digital tools
played an important role in coordinating and amplifying dissent. In Syria,
where protests most unexpectedly erupted in March 2011, Facebook and
Twitter were critical organizing nodes for the Friday protests that
eventually threatened the authoritarian regime of Bashar Al-Asad
(Blanford, 2011).
Conclusion
Egyptian and Tunisian digital activists have made persistent attempts to
undermine repressive and corrupt state structures that are deeply
implicated in social inequality. Their success in supporting and
amplifying movements to change those structures thus gives those
activists, as Durkheim would argue, a positive moral dimension that a
narrow focus on the digital divide would obscure. In other words, even if
access to digital technologies is unequal, elites have used their privileged
access to fight for a series of changes that they believe will redound to the
broad benefit of society. This is particularly true because the Middle East
is a region still characterized, even after the Arab Spring, by nondemocratic or proto-democratic governments that have proven unequal
to the task of broad economic development with prosperity shared by all
citizens. In most cases, it seems clear that the benefits of digital diffusion
have been captured by classes and population segments who already
occupy a privileged position in these societies. Despite the claims of
digital enthusiasts, it is not clear that the astronomical increase in rates
of digital penetration in the 2000s has had any discernible effect on
extant social inequalities in the states of the Middle East. In poorer
countries like Egypt, Syria, and Algeria, a great deal of economic activity
remains beyond the reach of the state, and thus largely outside of stateplanned projects for digitally enhanced economic development.
However, from a functionalist perspective, it is clearly possible to see the
contribution of social media to economic change and political
development. Access to alternate forms of digital media has proven
critical to the formation of what I have called “social media networks” –
loosely linked, non-hierarchical networks of activists and dissidents that
cross class, religious and national boundaries across the region (Faris,
2013). These Social Media Networks were critical actors in a drama that
unfolded over the course of the past decade in Egypt, Tunisia, Bahrain,
and elsewhere: the collation and organization of dissent in closed
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Digitally divided we stand 219
societies. While states adopted different policies toward digital activism
– with Tunisia extensively filtering and blocking political Web sites, and
Egypt merely harassing practitioners – the activists themselves were able
to adapt to these differing architectures of control to exert significant
influence on public debate, and to use the evolving ecosystem of social
media platforms to continue organizing protests and rallies that
contested the arbitrary nature of state power in these societies. Those
architectures of control, and the legal frameworks that govern access to
the Internet, will remain both a topic of extensive debate in the coming
years, and will affect the ability of activists to use digital tools for the
common good (MacKinnon, 2012).
In sorting through the ultimate effects of digital media, it remains true
that those best positioned to capture the benefits of new media
technologies will be the immediate beneficiaries. As Ronald Deibert
argued 15 years ago, “the properties of a communications environment—
the unique ways in which information can be stored, transmitted, and
distributed in that environment—‘favor’ the interests of some social forces
and ideas over others” (1997, p. 30). For the past ten years, digital media in
the Middle East has benefitted social forces and contributed to the
progressive ideas of elite, networked dissidents – middle class and upper
middle class activists who have been able to harness the power of digital
technologies for the purpose of undermining and challenging what had
seemed to be hegemonic state power. That means, of course, that many
people have been excluded from this nascent public sphere, and that
concerns about poverty and equality have not typically received the same
level of attention by these activists as issues about torture, corruption and
arbitrary state power. In many ways this allows us to confirm materialist
assumptions about the disparate impact and use of these technologies (as
well as culturalist understandings about the particular ways that women
are excluded from power and society in the Middle East), and to
understand that simple diffusion of Internet access and wireless
technologies will not, in and of themselves, undermine entrenched gender
hierarchies or class relations. Digital media both reflect and reinforce
certain inequalities, but at the same time, they offer elites the opportunity
to subvert dominant paradigms and discourses, and to organize dissent
even under stifling conditions of authoritarianism. And we should not be
surprised if, at some point in the future, these tools are married to a
project of class and gender equality that includes not just the Twitterati but
also people who have thus far been excluded from the general march of
progress.
References
The Arab Social Media Report. (2012). Dubai, United Arab Emirates: Dubai
School of Government.
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220 David M. Faris
Bellin, E. (2004). The robustness of authoritarianism in the Middle East:
Exceptionalism in comparative perspective. Comparative Politics, 36 (2), 139–157.
Blanford, N. (2011). On Facebook and Twitter, spreading revolution in Syria.
Christian Science Monitor, April 8, 2011.
Deibert, R. J. (1997). Parchment, printing and hypermedia: Communication in world
order transformation. New York: Columbia University Press.
de Koning, A. (2006). Café latte and Caesar salad: Cosmopolitan belonging in
Cairo’s coffee shops. In D. Singerman and P. Amar (eds.), Cairo cosmopolitan:
Politics, culture and urban space in the new globalized Middle East. Cairo, Egypt:
American University in Cairo Press.
Durkheim, E. (1984). The Division of Labour in Society. New York: Palgrave, 23–24.
Etling, B., Faris, R. and Palfrey, J. (2009). Mapping the Arab blogosphere: Politics,
culture and dissent. Berkman Center Research Publication, 2009–06, 1–62.
Fahmy, E. I. and Rifaat, N. M. (2010). Middle East information literacy awareness
and indigenous Arabic content challenges. International Information & Library
Review, 42 (2), 111–123.
Faris, D. (2012). Beyond social media revolutions: The Arab Spring and the
networked revolt. Politique etrangere 77, (1), 99–109.
Faris, D. (2013). Dissent and revolution in a digital age: Social media, blogging and
activism in Egypt. London: I.B. Tauris & Co.
Gini Index. (2011). World Bank development indicators, 2011. Retrieved from http://
data.worldbank.org/indicator/SI.POV.GINI (accessed May 30, 2012).
Hindman, M. (2008). The myth of digital democracy. Princeton, NJ, US: Princeton
University Press.
Open Net Initiative. (2009). Internet filtering in the Middle East and North
Africa. Retrieved from http://opennet.net/research/regions/mena (accessed
May 30, 2012).
Khamis, S. and Vaugh, K. (2011). Cyberactivism in the Egyptian revolution: How
civic engagement and citizen journalism tilted the balance. Arab Media and
Society, 14 (3).
Lynch, M. (2012). The Arab uprising: The unfinished revolutions of the new Middle East.
New York: PublicAffairs.
MacKinnon, R. (2012). Consent of the networked: The worldwide struggle for Internet
freedom. New York: Basic Books.
Norris, P. (2002). Digital divide: Civic engagement, information poverty and the Internet
worldwide. Cambridge, UK: Cambridge University Press.
Posusney, M. P. (2004). Authoritarianism: Middle East lessons for comparative
theory. Comparative Politics, 36(2), 127–138.
Radsch, C. (2012). Unveiling the revolutionaries: Cyberactivism and the role of women in
the Arab uprisings. Houston, TX, US: James A. Baker III Institute for Public
Policy, Rice University.
Schleusener, L. (2007). From blog to street: The Bahraini public sphere in
transition. Arab Media and Society, 1 (1).
Sil, R. (2000). The foundations of eclecticism: The epistemological status of
agency, culture and structure in social theory. Journal of Theoretical Politics,
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Tufekci, Z. and Wilson, C. (2012). Social media and the decision to participate in
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62, 363–379.
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Digitally divided we stand 221
Wheeler, D. (2003). Egypt: Building an information society for international
development. Review of African Political Economy, 98, 627–642.
Witte, J. C. and Mannon, S. E. (2010). The Internet and social inequalities. New York:
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Note
1 Interview with Afef Abrougui, Tunis, Tunisia, July 27, 2011.
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14 Explaining digital
inequalities in Israel
Juxtaposing the conflict and
cultural perspectives
Gustavo Mesch
Ilan Talmud
Tanya Kolobov1
University of Haifa
There are many scholarly concerns that the Internet, rather than reducing
existing inequalities, is actually exacerbating them (DiMaggio et al., 2001;
van Dijk, 2005). “Digital inequality” refers to the uneven access to and use
of information and communication technology (ICT) (Anderson et al.,
1995). With the advent of the World Wide Web, early studies of “digital
inequality” focused on understanding the factors associated with physical
access to the Internet at home, at work and in other settings (Hargittai,
2007). As Internet access has become more universal in Western societies,
studies have focused on more subtle indices of use, including the quality of
access, the context and intensity of use, types of use, and users’ computer
skills (van Dijk, 2005; Hargittai, 2007).
Ethnicity is an important dimension of both social and digital inequality
in multi-ethnic societies. Studies on the digital divide have shown that
ethnic minority groups are less likely to access and use the Internet
(Dupagne and Swalden, 2005; Fairlie, 2007; Mesch and Talmud, 2011).
Various factors have been identified as the antecedents of these
inequalities, most notably: income, educational level, occupational
standing, and attitudes toward technology (Witte and Mannon, 2010;
Mesch and Talmud, 2011). Thus, ethnic disparities in ICT access may
reflect social-structural disadvantages and cultural differences. The
purpose of this study is to investigate the sources of gaps in access to and
use of the Internet among ethnic groups in Israel. The study focuses in
particular on the differential contribution of ethnicity, human capital,
occupational structure and attitudes to ICT accessibility and use.
The context: Israel as a deeply divided society
Israel is a multi-ethnic society. Approximately 79 percent of the population
is Jewish, and the remainder is Arab. Jewish immigrants have come to
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Explaining digital inequalities in Israel 223
Israel in a sequence of waves. As a result, the Jewish population consists of
various groups from different backgrounds (Lewin-Epstein and Semyonov,
1993). The establishment of the Jewish state in 1948 and the Arab-Israeli
wars that followed left the Arab minority subordinated to the Jewish
majority, and in an inferior position in the Israeli economy and labor
market. The Arab minority is disadvantaged in its educational level and
socio-economic status (Okun and Friedlander, 2005). The result is that
while Jews are overrepresented in higher status occupations, and are more
likely employed in professional, scientific, and managerial positions, Arabs
are overrepresented in skilled and unskilled manual occupations (Kraus
and Yonay, 2000). This disparity accounts in part for the income
differences between Jews and Arabs (Lewin-Epstein and Semyonov, 1993).
Residential segregation also plays a role in the digital divide in Israel. Most
of the Arab population lives in peripheral areas of the country and in
small localities in which they are the vast majority of the population. Partly
because of state policies, Arab communities are allocated fewer resources
and have a less well developed infrastructure (Mesch et al., 1998; Smooha,
2002).
Another important group in the Israeli population is immigrants from
the former Soviet Union (FSU). Immigration to Israel took place in two
waves. The first was between 1968 and 1979, when 150,000 Jews arrived in
Israel. The second large wave of immigration began after 1989, shortly
after the dissolution of the Soviet Union. Since then, an estimated one
million immigrants from the FSU have arrived in Israel, becoming 15
percent of the total population and 20 percent of the Jewish population.
Some sociologists have concluded that because of their high degree of
residential and social segregation, and high level of language and culture
conservation, the FSU immigrants have become a new ethnic group (AlHaj, 2004).
Thus, the multi-ethnic nature of Israeli society, and the high level of
residential and social segregation of Arabs and immigrants makes Israel a
perfect setting for conducting this study on social position and the pattern
of access to and use of computer mediated communication.
Internet technology in Israel
In Israel, the proportion of users of computers from any place (home, work,
elsewhere) increased from 47 percent of the population in 2002 to 58
percent in 2006. In 2006, 63 percent of the Jewish population reported
having access to the Internet, but only 35 percent of the Arab population
had such access (Central Bureau of Statistics, 2008a, 2008b). A recent survey
found that while 77.3 percent of the Jewish population reported they had
used the Internet in the last 24 hours, only 61.9 percent of the Arabs had
done so. On average, Internet users are online 16 hours a week. Cell phone
access to the Internet is limited but expanding. According to the same
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224 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
survey, while 28 percent of Israeli Jews had mobile access, only 20 percent of
the Arab population reported using a mobile device to access the Internet
(Amichai-Hamburger, 2011). Studies also reported differences in ethnic
groups with regard to how they use the Internet. Israeli Arabs are more
likely to use the Internet to access health information and online news,
while Israeli Jews are more likely to use the Internet for communication,
financial and consumption purposes (Amichai-Hamburger, 2011; Mesch,
Mano and Tsamir, 2011; Mesch and Talmud, 2011).
The sociological literature uses various perspectives for explaining
digital inequalities. Following the work of Witte and Mannon (2010), we
will adopt the cultural and conflict perspectives with a focus on ethnonational inequalities.
Inequality from a conflict perspective
According to the conflict perspective, Internet literacy is tightly linked
with the division of power in society. Such literacy is a contextual set of
skills and knowledge whose possession is mainly used to maintain class
advantage and class boundaries. In fact, knowledge and skills are examples
of effective exclusionary practices of the ruling groups. Even with the
advent of universal education, knowledge and skills are not distributed
equally in society. The unequal distribution of funding to schools, a
curriculum that appeals to the values of the upper and middle class, and
conditions of poverty imply that large segments of the population are
denied particular forms of knowledge and skills.
Internet access may have a similar effect, reproducing social divisions
even while we celebrate the equalizing potential of ICT (Witte and
Mannon, 2010). Without the development of actual Internet competencies,
access to the Internet may in fact veil enduring social inequalities. In their
study on the US, Witte and Mannon (2010) found that, without controlling
for measures of class (education and income), race had a statistically
significant association with going online the previous day. Blacks and
Asian Americans were less likely to go online. However, when measures of
social class were included, the effects of race became statistically nonsignificant. This result provides support for the conflict perspective by
showing that the negative effects of race and ethnicity on Internet use are
the result of social class.
We believe that an alternative reason for this effect is that in
multicultural societies, over and above other socio-economic factors,
ethnicity and occupational structure often overlap. Members of majority
groups are overrepresented in professional, scientific and managerial
occupations, and minorities are overrepresented in blue-collar and low
skilled occupations. Occupation is an important variable in explaining the
rate of adoption of technology as well as the effects of computers and the
Internet on income level (Reese, 1988; Brynin, 2006; DiMaggio and
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Explaining digital inequalities in Israel 225
Bonikowski, 2008). In addition to using ICT in the workplace, white-collar
workers are more likely to understand the potential uses and applications
of ICT. Therefore, they develop positive attitudes about these technologies
and through them help workmates solve technical problems (Reese, 1988).
In Israel, ethnic minorities are more likely to belong to economically
disadvantaged social groups who have blue-collar jobs. Therefore, they are
generally not exposed to ICT at work, do not have the social support
necessary to learn about using the Internet, and often cannot afford a
computer at home, or the necessary Internet connection hardware. This
argument suggests the reproduction of digital inequality through the
replication of existing inequalities in access to the occupational structure
and to ICT (Mesch and Talmud, 2011).
Following the arguments of the conflict perspective, we expect that
ethnic differences in the use of computers at work and access to the
Internet will be partially explained by the individual’s ethnic background
and occupational class. More importantly, though Israel is characterized
by status group politics where ethnic background plays an increasing role
(Arian and Talmud, 1991; Smooha, 2002; Al-Haj, 2004) we expect that the
individual’s occupation serves as a structural container of attitudes,
literacy, and skills, and thereby would contribute in explaining the
observed variation in digital divide, over and above the pronounced effect
of income and education.
Inequality from a cultural perspective
The cultural perspective focuses on the multi-dimensional nature of
inequality. As presented by Witte and Mannon (2010), the cultural
perspective has its roots in the work of Max Weber’s distinction between
class and status. The latter reflects stratification according to lifestyle and
consumption. Specifically, restrictions on social interactions set highstatus group members apart from non-members: stratifying society along
social lines. According to this view, status stratification rests on social
prestige, rather than on mere economic assets. Once established,
distinctions in status are converted into particular lifestyles and
approaches to conducting one’s life. Distinctions in status are important
because they define the lens that people use to create their worldview.
From the cultural perspective, even class is not simply a structural position
relative to markets, but a shared perspective that defines and enables
patterns of social interaction among individuals with a common social
background. Thus, according to this perspective, social status is associated
with the lifestyles, values, and attitudes that are characteristic of each class
position in the stratification system.
Members of each class have a body of tacit knowledge including
attitudes, habits, and a deep understanding of “information orders” (Ryan,
2006). Such knowledge is not easily attained, but it constitutes the cultural
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226 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
(or symbolic) capital by which social actors deploy their “habitus” (shared
or taken-for granted mental models or “doxa”) of the world (Bourdieu,
1984; Calhoun et al., 1993). According to this view, attitudes toward
technology and digital competency are key factors in mastering the digital
field and benefitting from the advantages of ICT use (Calhoun et al.,
1993).
At the very core of a group’s habitus (doxa) are the building blocks of
lifestyle and consumption. The habitus provides a unique environment for
evaluating the social role of information and communication technologies.
From the cultural perspective, social prestige and the inter-generational
transmission of lifestyles are important for the shared understanding of
social inequality. The focus of this perspective is on the relationship
between occupational prestige and Internet use. Witte and Mannon (2010)
considered the extent to which the Internet may be viewed as a feature of
middle class or upper middle class lifestyle, and as a cultural boundary
marking the class divide. In this study, we look at central factors that play
an especially important role in distinguishing one’s status position, and
hence, one’s lifestyles choices: occupational prestige and attitudes toward
Internet use.
According to the cultural perspective, to the extent that the Internet is
associated with prestige and status, individuals in high prestige
occupations and individuals from prestigious families should be more
likely to use the Internet on a daily basis. These effects should be
independent of class differences, understood here as income and
education. In addition, if status implies consumption and lifestyle, then we
should see a positive association between occupational prestige and the
use of the Internet across a variety of domains, in consumption as well as
in production, and for purposes of communication as well as information.
Attitudes toward technology reflect a worldview (or habitus)
associated with social status. Theoretical models of technology adoption
have suggested that attitudes toward technology play an important role
in accessing and using information and communication technologies
(Rogers and Kincaid, 1981; Porter and Donthu, 2006). More specifically,
the technology acceptance model (TAM) suggests that perceived
attributes of the technology such as perceptions about the benefits of the
technology and its ease of use influence attitudes toward and use of
the technology (Porter and Donthu, 2006). The central assumptions of
the model are that the adoption and use of ICTs are associated with
positive attitudes that it turn are associated with a greater likelihood of
access to ICT. In a similar vein, Internet anxiety, such as expressing
negative feelings and attitudes about ICT and its effect on society, are
negatively associated with the likelihood of access and the frequency of
ICT use (Meuter et al., 2003). Negative attitudes toward computers and
the Internet were found more frequently in low income and minority
groups (Jackson et al., 2001).
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Explaining digital inequalities in Israel 227
Certainly, attitudes are related to social status. Social groups vary in
their attitudes toward technology, according to their position in society
(Jackson et al., 2001; Porter and Donthu, 2006). More specifically,
disadvantaged minorities may hold negative attitudes toward technology
as a reflection of their disadvantaged social position. Supporting this
argument, a study that investigated the effect of socio-demographic
characteristics on the adoption of the Internet found that age, education
and income were associated differently with attitudes and beliefs about
the Internet, and that beliefs mediated respondents’ attitudes to, and
ultimately use of, the Internet (Porter and Donthu, 2006). In addition,
due to their disadvantaged position in society, ethnic minorities are less
likely to be exposed to new technologies such as the Internet. A lack of
exposure to technology influences one’s self-concept (Reese, 1988;
Dupagne and Swalden, 2005). Jackson et al. (2001) argued that minorities
often internalize the stereotypes conveyed by the majority. According to
this viewpoint, a social stereotype linking minority status with poor
performance in technological domains may cause group members to
avoid engaging with that domain. Jackson et al. (2001) found that
minority groups are less likely to use ICTs because of a higher level of
negative attitudes toward ICT. In that sense, their lack of exposure may
lead to anxiety about, and fear and mistrust of, ICTs, causing them, in
turn, to avoid their use. The argument of the cultural perspective implies
that occupational prestige and attitudes toward ICT will be positively
associated with access to and variations in ICT use. Individuals in high
prestige occupations and individuals from prestigious families should be
more likely to hold positive attitudes toward ICT and use it on a daily
basis. These effects should be independent of class differences,
understood here as income and education.
Additional variables
There are additional variables that may be associated with access to and
use of ICT. Many studies have found a negative relationship between age
and Internet use (e.g., Kraut et al., 1998), with younger people being more
likely to go online (Rogers and Kincaid, 1981). ICT literacy, meaning the
degree of software competence, and the ability to use the Web are clearly
conversely related to age (Hargittai, 2007; Gilleard and Higgs, 2008).
Several other studies also found gaps between men and women in Internet
use (DiMaggio et al., 2001; 2004), claiming that male dominance in the
quantity and quality of usage reflects cultural stereotypes in Western
society. While in the past, several studies revealed a direct relationship
between gender and Internet access and ICT use, the gender gap in ICT
access appears to be disappearing. Nevertheless, a gender gap clearly
remains, at least in terms of the Internet user’s type of activity if not
duration of use (van Dijk, 2005).
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228 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
Data
The data for this study were gathered during the months of April–May
2009, and are part of a larger longitudinal study on the association
between Internet use and social capital. The Statistical Unit at the
University of Haifa created a sampling frame, containing a random sample
of the population of the State of Israel. The sampling frame included the
various groups that comprise the Israeli population. The unit contacted
2,792 households and conducted telephone interviews in Hebrew, Russian,
and Arabic. Of those contacted, 620 refused to be interviewed, 306 found
it difficult to understand the questionnaire and 100 did not complete the
interview. Overall, 1,792 valid questionnaires were obtained, and the
analysis is based on them.
When investigating the role of income, education, occupational
prestige and ethnicity on Internet use, a complex relationship between
the independent variables can be expected. In deeply divided societies,
ethnicity is likely to be highly correlated with education, income, and
occupation. Thus, multicollinearity might be problematic in the
multivariate analysis. We inspected the correlation matrix of all the
independent variables, and did not find any bivariate correlation higher
than 0.40. The highest values were between occupational prestige and
income, and between education and occupational prestige (p=0.36).
Other correlations were much lower. In addition, we conducted an
exploratory factor analysis to investigate whether education, income and
occupational prestige were part of single underlying latent variable. The
analysis resulted in three independent factors. We concluded,
accordingly, that statistical multicollinearity did not seem to be a
problem that either harmed the estimates’ precision or limited the
validity of the analysis.
Results
Table 14.1 presents data about physical access to ICT by ethnic group, and
indicates the existence of statistically significant differences in computer
use at home, at work and Internet use. Israeli Jews report the greatest use,
followed by immigrants from the FSU. Israeli Arabs are the least frequent
users in every category. Such findings confirm the existence of digital
inequality among social groups.
After documenting the differences in ICT use, the next task was to
investigate whether the conflict and cultural perspective can account for
these differences. In this next step, we conducted a logistic regression
analysis predicting Internet use. Model 1 includes only the variables
derived from the conflict perspective – education and income. Model 2
adds the variables from the cultural perspective – occupational prestige
and attitudes toward the Internet.
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Explaining digital inequalities in Israel 229
Table 14.1 Descriptive statistics of computer use and Internet use by social group
Variables
Population Group
Jews
– Nonimmigrants
%
Jews
– Immigrants
from the FSU
%
F
Total %
Arabs %
Computer
use at home
80.3
74.9
70.0
8.6**a
77.8
Computer
use at work
57.7
41.0
32.3
39.7**b
51.3
Computer
use
anywhere
84.3
76.4
72.2
14.51**c
81.3
Internet use
73.9
71.3
63.6
6.9**d
71.8
N
1270
195
327
* p < 0.05, ** p < 0.01
a Difference between: Jews – Non-immigrants and Arabs
bDifference between: Jews – Non-immigrants and Jews – Immigrants from the FSU, Jews
– Non-immigrants and Arabs
cDifference between: Jews – Non-immigrants and Jews – Immigrants from the FSU, Jews
– Non-immigrants and Arabs
d Difference between: Jews – Non-immigrants and Arabs
The results of the first model do not provide empirical support for the
conflict perspective. The effects of income and virtually all of the
occupational categories are statistically non-significant. The only effect
that is statistically significant – providing partial support for the conflict
perspective – is the positive effect of education. However, the most
impressively salient outcome is that even when occupation, income, and
education (as well as other variables) are controlled, the effect of ethnicity
persists. Thus, ethnicity has a direct net effect on Internet use, over and
above other indicators of social hierarchy. In other words, social class
alone does not explain why Israeli Arabs are less likely to use the Internet.
The second model introduces measures derived from the cultural
perspective – occupational prestige and attitudes toward technology. The
effect of these variables is statistically significant. Most importantly, when
these variables are introduced, the effect of ethnicity becomes statistically
non-significant, indicating that ethnic differences in Internet use in Israeli
society appear not to be related to income and occupational differences
between groups. Instead, these differences seem to arise from different
cultural orientations rooted in the status hierarchy, and associated with
hierarchically conceived lifestyles and occupational prestige. Furthermore,
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230 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
Table 14.2 Logistic regression, predicting Internet use at home according to class
variables (education, income) and cultural variables (occupational
prestige, attitudes towards technology)
Model 1
B
Model 2
SE
Odds
B
SE
Odds
–0.02
0.008
0.97**
Age
–0.02
0.007
0.97
Marital Status
(1=married)
–0.45
0.22
0.63*
–0.24
0.23
0.78
Gender (1=male)
0.37
0.21
1.45
0.03
0.22
1.03
Education
0.19
0.04
1.21
0.14
0.04
1.15**
Income (log)
0.68
0.35
1.97
0.76
0.39
2.15
Low grade professionals
0.42
0.33
1.51
0.52
0.35
1.69
Routine non-manual
laborers
1.077
0.42
2.93*
0.97
0.45
2.64*
Small employers and self
employed
0.50
0.46
1.65
0.43
0.49
1.54
Technicians and
workers3
0.73
0.47
2.08
0.73
0.51
2.08
0.02
0.008
1.02**
**
**
High grade professionals
Occupational prestige
Immigrants from the
FSU
Israeli Arabs
0.64
0.36
1.89
0.60
0.39
1.82
–0.60
0.25
0.54
–0.43
0.26
0.64
–0.98
0.10
0.37**
–0.01
1.28
0.98
**
Attitudes
Constant
Naglerke Pseudo
R-square
–0.88
0.18
1.20
0.41
0.32
*p < 0.05, ** p < 0.01
Note: High grade professionals is the dummy category of comparison.
the introduction of the cultural variables substantially increases the
explained variance of the model from 0.14 to 0.32 (p < 0.001).
The cultural perspective assumes that status is a central cause of social
hierarchy, and a reflection of social inequality. Occupations differ from
one another not just in terms of their salaries, but also in terms of the
lifestyles and mental models they bring in their wake (Bourdieu, 1984;
Calhoun et al., 1993). Hence, occupational prestige is ultimately a
determinant of Internet use.
In the next model, we examined this hypothesis further by conducting a
multivariate regression, predicting negative attitudes toward the Internet.
In this analysis we expected to find that to the extent to which the
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Explaining digital inequalities in Israel 231
predictions of the cultural perspective hold, occupational prestige and
ethnicity would each have an independent effect on attitudes toward the
Internet.
Table 14.3 presents the results, indicating that both perspectives play a
role in explaining negative attitudes toward the Internet. Education and
income have an independent (net) negative effect on attitudes toward the
Internet. The findings show that the higher the level of education and the
higher the amount of reported income, the less negative the attitudes
toward the Internet. Occupation is not associated with attitudes toward
the Internet. However, as expected by the cultural approach, occupational
prestige and ethnicity are significantly associated (in the expected
direction) with attitudes toward the Internet. In other words, the higher
the occupational standing, the lower the level of negative attitudes toward
the Internet. Finally, Israeli Arabs and immigrants from the FSU express
more negative attitudes toward the Internet than Israeli Jews.
An additional hypothesis, derived from the basic assumptions of the
cultural perspective, is that Internet use represents variations in the
lifestyle of various status groups in the population. According to this
perspective, different groups will use the Internet differently. We tested
this hypothesis by conducting a multivariate analysis, predicting five
different types of Internet use from the indicators of social class, and from
Table 14.3 OLS regression, predicting attitudes toward the Internet
B
β
SE
Age
0.004
0.002
0.055
Marital Status (1=married)
0.24
0.06
0.11**
Gender (1=male)
–0.32
0.06
–0.17**
Education
–0.05
0.01
–0.16**
Income (log)
–0.13
0.11
–0.03
High grade professionals
—
—
—
Low grade professionals
0.03
0.09
0.01
Routine non-manual laborers
–0.28
0.12
–0.12*
Small employers and self employed
–0.16
0.14
–0.05
Technicians and workers
–0.13
0.13
–0.05
Occupational prestige
–0.008
0.002
–0.17**
Immigrants from the FSU
–0.20
0.09
–0.06*
Israeli Arabs
–0.20
0.09
–0.06*
Constant
0.98
0.25
—
Adj. R-square
0.10
—
—
**
*p < 0.05, ** p < 0.01
Note: High grade professionals is the dummy category of comparison.
The Digital Divide_BOOK.indb 231
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232 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
the variables associated with status and ethnicity. Table 14.4 presents the
results. One very salient outcome is that both education and occupational
prestige are positively associated with most of the examined activities.
Education is positively associated with user-generated activities (using a
social networking site, etc.), with financial activities (checking and
conducting banking activities online), and with searching for information
and communicating using e-mail. Occupational prestige is positively
associated with four out of the five activities (including creating a
homepage, banking online, and online information searching and
communication). This finding provides more support for the cultural
perspective. More to the point, immigrants from the FSU are more likely
to be involved in Internet activities that deal with production (creating a
Web site) and information searching than native-born Israeli Jews.
Similarly, Israeli Arabs are more likely to be involved in information
searching only. By contrast, Israeli Jews are more likely to be involved in
the construction of user-generated content such as social networking,
online banking, and communication, and less likely to be involved in
information searching.
Discussion
The purpose of this study was to apply the conflict and cultural
sociological perspectives to the study of digital inequality in Israel. We
focused on the explanation of ethno-national variations in access,
attitudes, and types of use. In this study, we showed that occupational
categories explain variations in the use of computers at work, as well as
differences in Internet access, over and above the effect of income and
education. We also showed that ethnicity explains differences in the use of
computers at work and access to the Internet, which are also partially
explained by one’s occupational class.
We found repeated and systematic evidence that one’s place in the
social hierarchy, particularly cultural factors that reflect habitus or
vertically situated lifestyles and mental models, predict Internet access and
use, and attitudes toward ICT. These practices of virtual reality are
embedded in other kinds of practices common to Israeli society, which are
typically attributable to other indicators of social prestige and ethnicity as
well.
Our findings tend to support the cultural perspective for explaining
inequalities in the use of digital technology. Despite the existence of
ethnic differences in the level of schooling and income between Arabs,
Jews from the FSU and native-born Israeli Jews, we found that the main
inequality in access was between Israeli Jews and Israeli Arabs.
Furthermore, this inequality was explained by variations in occupational
prestige and attitudes toward technology. However, the picture we portray
here is complex. On one hand, Israeli Arabs have a significantly more
The Digital Divide_BOOK.indb 232
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The Digital Divide_BOOK.indb 233
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0.25
0.28
0.27
0.18
0.71
0.08
—
0.22
0.39
0.01
0.47
0.11
1.46
0.02
High grade
professionals
Low grade
professionals
Routine nonmanual laborers
Small employers
0.30
and self employed
0.44
Income (log)
Technicians and
workers
Occupational
prestige
Immigrants from
the FSU
Israeli Arabs
Constant
Adj. R-square
0.003
0.42
0.19
0.38
–0.05
—
0.70
0.06
0.46
0.02
0.82
0.476
0.12
0.21
0.22
**
0.006
0.31
0.33
0.29
0.22
—
0.27
0.02
0.14
0.15
–0.88
0.08** –0.25
0.12*
0.09
0.04
0.10
0.05
—
0.01
0.06
0.07*
–0.005 –0.47
0.01
0.26
0.42
0.67
0.29
0.08
2.74
–0.13** –1.01
–0.03** –0.01
0.03
0.07
0.02
0.07
–0.01
—
0.08
0.60
0.15
0.16
**
0.004
0.23
0.24
0.21
0.16
—
0.19
0.23
**
—
0.01
0.05
**
0.08
0.10
0.11
0.28
0.02
SE
β
B
–0.22**
–0.003
0.15**
0.06
0.07
0.19**
0.07
—
0.04
0.10
**
0.04
1.84
0.27
0.33
0.008
0.13
**
0.46
0.11
0.12
0.003
0.17
0.18
0.16
0.07
0.16
0.12
—
0.15
0.01
0.08
0.08
0.07
—
–0.09
0.04
0.09** –0.08
0.007 –0.18
β
B
0.02
0.47
0.60
0.74
0.13
—
0.35
0.07
–0.02
0.11
–0.13
0.08** –0.61
0.08** –0.11
0.14**
0.04
0.04
0.03
0.02
—
–0.02
0.11
**
–0.03
–0.07* –0.03
0.003 –0.09** –0.009
SE
Search for information
0.004 –0.13** –0.008
0.11**
–0.10**
* p < 0.05, ** p < 0.01
Note: High grade professionals is the dummy category of comparison.
*
0.19
0.005
0.19
—
0.23
0.02
0.03
Education
0.12
0.24
0.13
Gender (1=male)
–0.02
Marital Status
(1=married)
B
Check bank account
0.006 –0.19** –0.01
SE
β
B
0.005 –0.12** –0.04
SE
β
–0.01
Age
B
Create an SNS site
Create a home page
Table 14.4 OLS regression, predicting conducting Internet activities
β
0.58
0.14
0.15
0.004
0.22
0.23
0.20
0.15
—
0.19
0.01
0.10
0.10
–0.13**
–0.02
0.33**
0.12*
0.10**
0.21**
0.03
—
0.06*
0.15**
–0.008
–0.01
0.004 –0.07*
SE
E-mail
234 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
negative attitude toward ICTs, net of the pronounced effects of income
and education. Nevertheless, their lower rate of digital access is mainly due
to their disadvantaged social status. In this sense, ameliorating the
economic inequality between ethnic groups is likely to reduce the digital
divide between Israeli Jews and Israeli Arabs. Future research should
expand the exploration of the conflict and cultural perspectives in a more
refined way.
The study has various limitations. As we noted, over time there has been
a reduction in the differences in access to ICT. This reduction and the
extent to which it affects more affluent sub-groups of Arabs could not be
investigated here as we relied on a cross-sectional data set. Furthermore,
future longitudinal studies should focus not only on the determinants of
social inequality, but also on its consequences in terms of the attainment
of status and the acquisition of social capital.
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236 Gustavo Mesch, Ilan Talmud and Tanya Kolobov
Note
1 All of the authors have contributed equally to the writing of this chapter. The
research was supported by a grant from the Israel Science Foundation
(#1014/08). Direct all correspondence to Gustavo S. Mesch, Department of
Sociology and Anthropology, University of Haifa, Israel. E-mail: Gustavo@soc.
haifa.ac.il
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15 An analysis of the secondlevel digital divide in Iran
A case study of University of
Tehran undergraduate students
Hamid Abdollahyan
University of Tehran
Mehdi Semati
Northern Illinois University
Mohammad Ahmadi
University of Tehran
Introduction
This chapter offers a descriptive analysis of second-level digital divide in
Iran with a special reference to the case of second-level digital divide
among University of Tehran students. After explaining the problematic of
the paper, we will introduce second-level digital divide as a conceptual
framework that can explain and address second-level digital divide as a
larger problematic within Iranian society. Then we will offer the
methodology of this research that is in line with our conceptual
framework. Finally, we will present an analysis on the empirical data that
was collected through a survey study of undergraduate students of the
University of Tehran.
Problematic of research
Along with the development of the Internet and its use since the early
1990s there was an increasing interest among scholars in researching
inequalities in Internet use by focusing mainly on the distinction between
information haves and have-nots (Sassi, 2005; Yu, 2006; Crenshaw and
Robison, 2006; Livingstone and Helsper, 2007). Various scholars later
conceptualized this distinction as digital divide, which produced
numerous books and papers on the topic of digital divide. From the early
years of the twenty-first century, however, a new turn began to take shape
regarding the study of inequalities caused by the development of new
media technologies (e.g., Abdollahyan and Ahmadi, 2011).
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238 Hamid Abdollahyan, Mehdi Semati and Mohammad Ahmadi
The main idea supporting these new studies revolved around the fact
that mere access to the Internet does not mean there is a uniform use of
the Internet, and mere use of the Internet does not mean every user
equally enjoys the opportunities available to them. Among the new
concepts there was also the “second-level digital divide,” which referred to
the inequalities of Internet use among the users. Each research project
pointed out a different type of inequality among the users, including
inequality of usage based on age (Bonfadelli, 2002), gender (DiMaggio et
al., 2001; Herring, 2001), economic and social status (Wilson et al., 2003;
van Dijk, 2005) and education (Hargittai and Walejko, 2008; Hargittai,
2002) to name a few.
Generally speaking, however, there was a consensus among scholars
(e.g., Hargittai, 2002) to distinguish three levels of digital divide. First
there is a divide that is mostly noticeable between the poor and the rich
nations; then there is the second divide that exists between the poor and
the rich within the same society; finally, there is the third type of
inequality that exists between the skilled and the new users. Here, we
study various elements of the second-level digital divide within an
educational setting (the University of Tehran). When we started this
research our main objective was to identify differences of skills among
undergraduate students at the University of Tehran. Here we offer an
argument that concerns a different digital divide. We argue that in order
to get education and an occupation and to live in knowledge societies,1
the mere abilities to read, write and do simple arithmetic (i.e., traditional
literacy) are not enough and students need to acquire new set of skills.
Moreover, new media and the technological boom in recent decades
have made dramatic changes in the ways people interact with one
another, work together and so on. As van Dijk (2006a, p. 243) puts it, new
media are trend amplifiers and in this case they produce a wider skill
divide among the Internet users than ever before. We believe the secondlevel digital divide would provide a satisfactory and plausible concept
that can explain the skills gap between various groups of users in Iran
(see also Abdollahyan and Ahmadi, 2011).
Differences in skills can cause formation of new inequalities in the new
media world (Gui and Argentin, 2011). Therefore, access to the Internet is
not the only matter of concern in understanding the world of the Internet.
Rather, the differences in digital skills are a primary aspect of the secondlevel digital divide (Hargittai, 2002; van Deursen and van Dijk, 2010).
However, the question is why differences in skills are an issue. As
Hargittai (2004) emphasizes, even if higher access rates are achieved in
developing countries, large portions of certain populations would still not
be able to benefit from this medium. Accordingly, drawing the attention of
scholars and governments to such problems would help address the issue.
And, considering that Internet use in Iran is comparatively high (46.9
percent penetration, according to Internet World Stats, 2011), the
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An analysis of the second-level digital divide in Iran 239
following observations indicate that the second-level digital divide is an
issue in Iran and needs to be addressed.
The first observation concerns the changing patterns of Internet access
in Iran. Internet access is equally distributed across various groups.2 The
second observation refers to the gap between the Internet use and the new
skills needed for knowledge-based societies. In Iran, this gap becomes
more evident when one is involved in participatory observation of Internet
use. In addition, in the early years of the invention of the Internet the
digital divide was the main issue of concern, today there are more
concerns expressed about the ways people practically use the Internet
(Gilster, 1997; Hargittai, 2002, 2005, 2009; Eshet, 2002; Eshet and Aviram,
2006; Eshet-Alkalai, 2004; Eshet-Alkalai, and Chajut, 2009; Eshet-Alkali
and Amichai-Hamburger, 2004; Perez Tornero, 2004a, 2004b; Tyner, 1998;
New Media Consortium, 2005; Jenkins et al., 2006; Dobson and Willinsky,
2009; Livingstone and Helsper, 2010). In other words, the digital divide
has expanded to include the issue of utilization. Accordingly, the most
important issue of today is not whether there is access, or lack thereof, to
new media technologies. Rather, the major concern is recognizing the fact
that there is a divide between information haves and have-nots as a result
of lack of skills.
Some scholars (e.g., Norris, 2001) maintain that digital divide in
Internet use is not a new divide and it only mirrors existing inequalities in
use of communication technologies. In other words, such a divide is an
extension of the existing divides. Nevertheless, the increasing rate of
Internet use in Iran requires research and policies to go hand-in-hand in
order to offer plans for decreasing this divide and its socio-cultural and
economic consequences. In addressing such an objective, we first
conceptualize the second-level digital divide, and then report on our
empirical study to highlight the implications of this divide.
Conceptual framework
This study approaches the second-level digital divide in Iran through a
communication and sociological perspective. At the communication level,
it can be argued that the new studies on literacy and on studies related to
the effects of media literacy and media education now focus on addressing
the required skills and abilities to use new media technologies
(Livingstone and Helsper, 2010; Tyner, 1998; Warnick, 2002). Here we
emphasize the “differential possession of digital skills” (van Deursen and
van Dijk, 2010). Accordingly, we review some of the major works that seek
an explanation for new divides in knowledge societies.
Tsatsou (2011) categorizes four groups of digital divide studies: 1)
techno-centric, 2) economy-driven, 3) socio-cultural, and 4) policy
motivated. Van Dijk (2006b) refers to five different types of inequalities: 1)
technological inequality, which conceptualizes it in relation to
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240 Hamid Abdollahyan, Mehdi Semati and Mohammad Ahmadi
technological opportunities, 2) immaterial inequality, which is related to
life chances and freedom, 3) material inequality that involves various
forms of capital including economic, social, cultural capital, 4) social
inequality, which includes positions, power and participation, and finally;
5) educational inequality, which is related to capabilities and skills. Van
Deursen and van Dijk (2010) proposed a range of Internet skills including
operational Internet skills, formal Internet skills, information Internet
skills and strategic Internet skills. Van Dijk and Hacker (2003) also
distinguish between four types of access: 1) mental access, 2) material
access, 3) skills access, and; 4) usage access. Selwyn (2004) distinguishes
between access to ICT, use of ICT and meaningful use of ICT. He defines
digital divide as “a hierarchy of access to various forms of technology in
various contexts resulting in differing levels of engagement and
consequences.” Hargittai (2004) introduces multiple dimensions in digital
divide that include technological access, autonomy, social support, skill
and types of uses.
At the sociological level, we maintain that social capital is a more
important factor in Iran as a stratifying factor, although economic factors
play a role. This is the case because education has become widely available
in Iran, as the government has pursued a policy of education for the
masses for the past three decades (see Semati, 2008). The growing number
of educational institutions, including universities, most of them subsidized
public universities available to individuals across different strata in Iranian
society, has entailed a growing population of pupils and university students
with access to the Internet either at the institutional sites or via personal
computers (ibid., 2008). Accordingly, we suggest that access to educational
settings and computers (i.e., being a student) is a key factor in digital
divide. A Weberian approach that emphasizes factors in stratification
beyond the economic factors is an appropriate framework.
Both from a communication perspective and a sociological one, we can
conclude that second-level digital divide is a skill-based divide and can
cause inequality of literacy in Iran, which in turn can cause other
inequalities across various groups. That is the reason we have chosen the
University of Tehran as a case in which digital divide can be studied and
used to think about the future and the divide in the larger context of the
Iranian society.
Methodology
This study falls into the category of user-oriented studies (Pinto and Sales,
2007). We conducted a survey to identify various digital skills among
undergraduate students from the University of Tehran. To design the
questionnaire we used Jolls and Thoman’s model of media literacy process
skills (2004; 2008). They present a set of five process skills that are
necessary to be able to live, study and work in a world saturated with (old
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An analysis of the second-level digital divide in Iran 241
and new) media. Their definition concerns media literacy process skills
and includes the abilities to “access, analyze, evaluate, create and
participate”.
We used self-assessment through questionnaire (Hargittai, 2002; 2005),
which is a suitable approach for large sampling. Based on Jolls and
Thoman’s (2004; 2008) definitions of media literacy process skills and our
understanding of digital skills according to the needs of Iranian students
we defined five process skills as follows:
1 Accessing ability, which refers to users’ ability to access information
and digital resources;
2 Analyzing ability, which refers to users’ ability to analyze the messages
and information students receive;
3 Evaluating ability, which refers to users’ ability to judge and evaluate
the credibility of information;
4 Creating ability, which refers to users’ ability to produce new contents
and not merely be consumers (becoming “prosumers”);
5 Participating ability, which refers to users’ ability to publish digital
contents and interact with other users.
In order to define these skills we focused on basic computer and web
operating skills. Based on each skill, we defined a set of sub-skills that
could measure University of Tehran undergraduate students’ digital
abilities. We considered the educational and professional necessities of
university students in Iran as various elements of the measurement and
placed them in the questionnaire. We put an emphasis on informationretrieving skills rather than communicative skills. Moreover, we considered
Web 2.0 related skills as being critical for students.
Operationalization and structure of the questionnaire
In order to examine the hypothesis and measure various levels of skills
and other variables we organized the questionnaire in such a way to
include the following items. A set of questions was considered to obtain
general personal information. These consisted of questions regarding the
samples’ gender, field of study, age, the starting date of university
education, and places of access to computers and the Internet. We also
used scales such as five-point self-reported ratings to measure the
familiarity of the samples with the following digital skills items: basic
knowledge of the English language for using computers, file compression,
reboot, preference settings, back up, modem, “save as”, Microsoft Word,
Microsoft PowerPoint, Microsoft Access, Microsoft Excel, JFV, PDF, JPG,
refresh/reload, add to favorites/bookmarking, spam, BCC in email,
Boolean operators (or, and), ISP, HTML, server, firewall, .gov, .org, the
Internet country code top-level domain, .ac (“academic”) second-level
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242 Hamid Abdollahyan, Mehdi Semati and Mohammad Ahmadi
domain, the Internet ads, cookie, mirror websites, e-zine, database, open
access journals, XML, Unicode, shareware, filtering software, wiki, feed,
RSS, blogging, podcasts and Proxypod.3 We also used questions to
measure the time samples spent on the web daily and years using the
Internet. In order to measure the digital skills of self-efficacy,4 we used the
following question: “Regarding your familiarity with computers and the
Internet, how do you evaluate your abilities?” (This was a five-point scale
consisting of a) not at all skilled, b) not very skilled, c) fairly skilled, d)
skilled; and, f) very skilled).
Sampling
For this study we used proportionate stratified sampling techniques (see
Ruane, 2005, pp. 114–115). We first acquired the total number of
undergraduate students (N=17,310) from the university’s Center for
Statistics and Informatics. Then we classified students based on their
majors and disciplinary affiliation. Eventually, we selected sample elements
in proportion to their actual numbers in the overall population of
undergraduate students. Based on this technique we arrived at a total
sample of 376 students.
Analysis and findings5
Descriptive data analysis
In our data analysis we used both descriptive and inferential statistics. At
the descriptive level, we offer an analysis of the demographic information
of the research sample. According to our data, 42.5 percent of the samples
were male and 57.5 percent were female students. The data showed that 70
percent of the respondents were between 20 and 22 years old, 18 percent
were 18 and 19 years old and about 12 percent were 22 years and older. The
data also indicates that 18.1 percent of the respondents were first year
students, 26.9 percent were second year, 23.1 percent in third year and 31.9
percent were fourth year BA students.
One important variable, however, is Internet use. According to the
research data, 74.2 percent of the respondents used the Internet in only
one place (mainly at home, school or the work place). While 24.7 percent
of the respondents used the Internet in two places, only a small percentage
(1.1 percent) used the Internet in three places. This means students at the
University of Tehran are dependent upon the university’s Internet
facilities.
On average, more than half of the respondents (56.6 percent) use the
Internet for up to one hour per day. Those who used the Internet for two
to three hours a day made up 31.4 percent of the users. About 12 percent
use it for more than three hours a day. We used daily usage to gauge the
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An analysis of the second-level digital divide in Iran 243
weight of the Internet use and our data indicates that about half of the
respondents have been working with the Internet for four to seven years.
About 25 percent started to work with the Internet seven to thirteen years
ago and less than 25 percent of the students started to work with the
Internet from three years to one year ago. This descriptive data indicates
that undergraduate students on average are professional users as over 75
percent of them have been familiar with the Internet for between four and
13 years.
Table 15.1 Distribution of frequencies based on daily Internet use
Daily use
Sex
Female
1 hour and less
Total
%
Male
123
90
213
56.6
2–3 hours
71
47
118
31.4
4–5 hours
17
21
38
10.1
6–7 hours
4
0
4
1.1
8–9 hours
1
1
2
0.5
10 hours and more
1
0
1
0.3
217
159
376
100.0
Total
Table 15.2 Distribution of frequencies based on Internet usage history
Usage history
Sex
Total
%
Female
Male
One year and less
12
10
22
5.9
2–3 years
27
20
47
12.5
4–5 years
59
51
110
29.3
6–7 years
59
38
97
25.9
8–9 years
40
27
67
17.9
10–11 years
18
11
29
7.7
12–13 years
1
2
3
0.8
216
159
375
100.0
Total
One of the female respondents did not answer this question.
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244 Hamid Abdollahyan, Mehdi Semati and Mohammad Ahmadi
Inferential data analysis
We calculated 41 digital skill-related items to form a “digital skills”
variable. Our data revealed that 62.2 percent of the respondents marked
“not at all skilled” or “not very skilled”. The percentage who reported that
they are “fairly skilled” was 18.9. Also, 18.9 percent marked “skilled” or
“very skilled”.
We also tested the possible causal relationship between various variables
and discovered that there is an association between the sex of the
respondents and their familiarity with digital skills, since the result of
JFV
podcasts
mirror websites
XML
feed
RSS
Proxyprod
Unicode
Boolean operators (or, and)
ISP
shareware
e-zine
cookie
open access journals
gov.
firewall
database
Internet ads
HTML
BCC in email
Microsoft Access
wiki
back up
ac.
reboot
filtering software
server
org.
spam
JPG
Microsoft Excel
file compression
preference settings
Internet country code top-modem
refresh/reload
PDF
add to favorites/bookmarking
blogging
basic English knowledge for using
Microsoft PowerPoint
Microsoft Word
“save as”
Digital literacy measures
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Figure 15.1 Means of digital skills items
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An analysis of the second-level digital divide in Iran 245
Cramer’s V test amounted to 0.16, indicating a positive association between
the two variables. We used 41 variables as indicators for measuring the
samples’ level of familiarity. According to the Lambda results of the 41
variables, it can be concluded that male students are slightly more familiar
with digital skills than female students are.
The data also indicates that there is a positive correlation between age
and familiarity with digital skills (R=245; E=0.01). This means that older
students report more familiarity with digital skills than younger ones.
Probably because more time spent at the university contributes to having
more opportunities for gaining new skills and having access to broadband
Internet facilities.
It can also be argued that based on the date of entering university, the
fourth and third year students indicated more familiarity with digital skills
than the second and first year students did. In addition, there is a positive
correlation between the length of the students’ study time and their
familiarity with digital skills (Kendall’s tau-c=0.2). The data also indicates
that there is a positive, though weak correlation (r=0.22) between owning
a PC or a Notebook and an increase or a decrease in digital abilities. There
is also a weak but positive correlation between places of access and
familiarity with digital skills. This means the students who have used the
Internet in two or three places (home, university, dormitory, work place,
etc.) are more familiar with the digital skills than others (see also
Livingstone and Helsper, 2010).
The data also revealed that there is a very strong and positive correlation
between time spent on the web daily and years of using the Internet on one
hand, and digital skills on the other. That means the students with more
daily usage time were more likely to report a higher level of familiarity
with digital skills than others (r=0.47). Moreover, students who started to
use the Internet earlier are more familiar with digital skills (r=0.47).
Further measures of self-efficacy show a strong correlation with real
skills of students (Kendall’s tau-b = 0.53). This means the students who
report higher digital skills in their five-point scale self-efficacy question
are also more familiar with the digital skills than those who had a lower
level of digital skills.
Analytical findings
We offer the following nine measures for predicting university students’
digital skills along with some results coming from application of such
measures:
1
Gender: male students reported more familiarity with the digital skills
than female students did;
2 Age: older students reported more familiarity with the digital skills,
although this might not be true beyond an educational setting;
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246 Hamid Abdollahyan, Mehdi Semati and Mohammad Ahmadi
3
Years of studying and living on campus: fourth and third year students
reported more familiarity with digital skills;
4 Owning a laptop or a desktop computer;
5 Number of places of access: the higher the number of places of access
available to a student, the more effectively he/she is able to use
computers and the Internet;
6 Time spent on the Internet daily: users with higher daily usage tend to
report more familiarity with digital skills;
7 Years using the Internet: students who started using the Internet
earlier than their cohorts tend to report more familiarity with digital
skills;
8 Digital skills self-efficacy: respondents who evaluate their digital skills
as “skilled” and “very skilled” are more familiar with digital skills;
9 The set of the digital skills measures: the set of 41 digital skills
measures, introduced and tested in this study give us the ability to
predict digital skills of university students.
Generally speaking, our measurement indicates that the second-level digital
divide is noticeable among undergraduate students of the University of
Tehran and among various age and gender groups. The findings also
indicate that the pattern of Internet use (years using the Internet) and the
amount of daily use of the Internet, and the possession of a laptop or a
desktop determine the factors affecting the second-level digital divide.
Conclusion
The research findings contribute to our understanding about the
mechanism of educational inequality in the University of Tehran. For
example, it is safe to claim here that a difference of skills among students
has caused an educational inequality as the prime source of inequality
among students. Differences in skills are important because, as Friemel
and Signer (2010) put it, such differences would produce non-egalitarian
use of the Internet applications and content, something that bring us to a
Weberian type of social stratification across Internet users in Iran.
Although it is generally taken for granted that younger Internet users
are very skilled, our study shows this is not necessarily true. With respect to
educational systems’ approaches toward new media technologies, in many
countries including Iran, funding and planning are more focused on
equipping educational institutions with new devices rather than helping
students develop a new approach toward new media technologies.
In terms of the techniques that we employed to produce such a
conclusion, it should be noted that the measures that we introduced and
tested in this study are developed in an educational environment. Using
such measurements for other socio-cultural environments, age groups or
for specific professional purposes would require some modifications.
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An analysis of the second-level digital divide in Iran 247
Also, there might be questions regarding censorship and how it could
have affected the research results. It should be noted here that our
research was conducted in an academic environment. Generally speaking,
censorship could deepen digital divide because more skilled users can
overcome censorship attempts (anti-filtering software, for example). Less
skilled users lack such abilities and that can affect their access and Internet
usage and produce more stratification. It should also be added that we
have observed that almost all known social networking and micro blogging
websites are subject to government blocking regulations in Iran.
Nevertheless, some 66.5 percent of the respondents reported they were
familiar with Internet forums and some 64.4 percent of them claimed to
have had access to social networking websites. We should add that our own
personal observations indicate that a large number of university students
are regarded as Facebook users although it is hard to provide reliable
statistics for that claim.
We are certainly aware that some of the inequalities we report in our
work follow similar patterns in other parts of the world. Issues such as
gender gap (DiMaggio et al., 2001; Herring, 2001), number of places of
access (Livingstone and Helsper, 2010), time spent on Internet and years
using the Internet (Hargittai, 2002, 2005) are among a few that seem to be
similar to what is addressed here. Nevertheless, this shows that, although
Internet penetration rate in Iran is lower than some advanced societies,
similar patterns in Internet usage exist. We also tried to make sense of it
and show how it might affect future generations in Iran.
Finally, there are some limitations to this study especially where units of
observations are concerned. We still need more studies on a national level
to measure digital divide in Iran in order to be able to make a conclusion
about Iran. We are aware that although access rates are growing in Iran, a
broadband divide is developing and this is where new measures are needed
to determine the dimensions of second-level digital divide.
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Perez Tornero, J.M. (2004b). A new model for promoting digital literacy. Available
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http://ec.europa.eu/education/archive/elearning/doc/workshops/
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2009).
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Oxford, UK: Blackwell.
Sassi, S. (2005). Cultural differentiation or social segregation? Four approaches to
the digital divide. New Media & Society, 7(5), 684–700.
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dynamic phenomenon. Information Society. 19, 315–326.
van Dijk, J.A.G.M. (2005). The deepening divide: Inequality in the information society.
Thousand Oaks, US: Sage.
van Dijk, J.A.G.M. (2006a). The network society (2nd edn). London: Sage.
van Dijk, J.A.G.M. (2006b). Digital divide research achievements and
shortcomings. Poetics, 34, 221–235.
Warnick, B. (2002). Critical literacy in a digital era: Technology, rhetoric, and the public
interest. Mahwah, NJ: Lawrence Erlbaum.
Wilson, K.R., Walin, J.S. and Reiser, C. (2003). Social stratification and the digital
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Information Science, 38(4), 229–252.
Notes
1 See Department of Economic and Social Affairs of the United Nations (2005).
2 According to the International Communication Union (ITU), however, the
latest statistics (2010) indicate that only a small percentage of the Iranian users
(0.68%) have access to broadband connections. This gap is something that
worries scholars of the field, as in the long term it could slow down Internet use,
causing issues in development projects in Iran.
3 In our questionnaire we put two bogus items (Proxypod and JFV) following
Hargittai’s model of inquiry (Hargittai, 2009). Although these two terms are
very similar to ICT terms, they express no meaning. Our findings indicate that
the mean of the bogus item JFV among 43 items was the lowest one, and the
mean of Proxypod was only higher than RSS, feed, XML, mirror websites,
podcast and JFV. That is probably because this item is similar to other ICT
terms. These results indicate that it is likely that the respondents did not answer
our questions in a haphazard way. That means they did not claim they are
familiar with items that do not exist. In order to evaluate the reliability of the
measures used in the questionnaire we conducted the Cronbach’s Alpha test.
The test result for 41 variables (items) minus the 2 bogus items amounted to
0.97, which confirms we used a highly reliable set of measures in the
questionnaire.
4 For arguments on self-efficacy see: Bandura (1977, 1994); Bandura and Locke
(2003); Bandura et al., (2001). And, for arguments on digital literacy selfefficacy see: Hargittai (2005, 2009); Livingstone and Helsper (2010).
5 The data was collected to assess the digital literacy of students. Here we tried
to apply a new theoretical framework to an existing set of data.
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Section 6
Under-studied countries
and regions
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16 The digital divide in the
Latin American context1
Daniela Trucco
United Nations Economic
Commission for Latin America and the Caribbean
Introduction
Durkheim’s sociological theory was developed a century ago, when the
modernization process of industrial society was perceived to be generating
a set of disintegrating processes; class conflicts, recurrent economic crisis,
increased suicide rates, lack of social values, etc. (Usátegui, 2003). This
social unrest had to be addressed through social regulating processes and
the generation of social integration; where the state and the education
system played a key role.
The main purpose of this chapter is to analyze from Durkheim´s
viewpoint, the contribution that educational public policy in Latin
America (LA) is making to society in the digital era. In one of the most
unequal regions of the world, the main risk is that the mass dissemination
of information and communication technologies (ICT) could be
generating new and rapidly growing differences. The approach views ICT
as instruments for addressing the development needs of the region
through the socialization process of children and adolescents of different
social sectors of society, contributing to the formation of human capital
assets in the more disadvantaged social sectors of LA´s society. However,
there are different types or levels of digital divides that operate
simultaneously. The access gap, which is still substantial, is compounded
by a second breach of use and appropriation. The analysis uses empirical
data collected through countries’ household surveys and through
international educational assessment tests like the OECD Programme for
International Student Assessment (PISA) (OECD, 2009).
The discussion focuses on the role that public policy can take on in
order to counter the consequences of market-driven mass dissemination of
ICT in terms of social integration (à la Durkheim). His perspective on the
role of the state, as representing society’s interest and education being a
key tool in this process is used to follow these developments in the region.
A strategic area is the public school system that can not only promote more
equitable access to technology but also its meaningful use and skill
development for generations to come.
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254 Daniela Trucco Horwitz
The inevitable process of Internet dissemination:
Risks and prospects
Countries of the LA region have not been exempt from the rapid
dissemination and incorporation of digital technologies – such as
computers and the Internet – in everyday life. Differential access through
the Internet to inconceivable amounts of information, with global reach
and no time barriers, should explain important changes in social
structures. Access to the Internet and to ICT devices also carries meanings
linked to their use, created and disseminated especially by advertising.
The most prominent of these is the promise of individual success through
a lifestyle involving their use in all daily activities. Whereas whoever lacks
access to these technologies appears doomed to stagnate and be
marginalized (UNDP, 2006).
The process of dissemination and use of these technologies has also
been the subject of public policies, as tools for development and effective
government service. Such public policies have further sought to offset
inequities of access by promoting a variety of initiatives to foster
widespread use (UNDP, 2006). The promotion of access to these
technologies through the education system has been one of the privileged
public policy strategies in this region.
Durkheim would have agreed with the importance given to the
education system as a strategic factor for social integration. Education was
conceived by the author as crucial for socialization, where society needs to
oversee that individuals acquire the common moral values and skills that
allow them to maintain collective life. Society cannot survive if there is not
enough homogeneity among its members; education perpetuates and
reinforces that homogeneity, fixing in advance the essential similarities
required by collective life in the child’s soul (Durkheim, 1975, as cited in:
Usátegui, 2003). Although not an opponent of private education,
Durkheim saw an important regulatory and supervising role of the state in
the education system. The state’s intervention is required if the goal is a
more equal society (Usátegui, 2003).
The education system has been conceived as a strategic port of entry
into the information and knowledge society. The first school-oriented ICT
policies and programs in LA emerged in the late 1980s and early 1990s,
under the assumption that they were tools that would address the major
challenges that countries faced in this field. Those challenges included
ensuring a high quality education, improving the efficiency of education
systems and guaranteeing equity in the different dimensions of those
systems (Sunkel and Trucco, 2010).
At the same time, ICT mass dissemination through market-driven
forces has been very rapid in recent years, especially in the richer countries
of the LA region, and the youngest generations are the ones that have
incorporated them to the greatest extent in their daily lives. However, as
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The digital divide in the Latin American context 255
expected in one of the most unequal regions of the world, it is a process
that has reproduced and even exacerbated the pre-existing social
inequities. As the data analysis will show in the following section, there are
different types or levels of digital divides operating simultaneously.
While access to the Internet presents a very equalizing potential, in
terms of information access around the world for all its users, it also has
the risk of reproducing social cleavages. The concept of a second digital
divide acquires relevance in this sense, which is related to the opportunity
of taking real advantage of the Internet’s potential in the development of
individual capabilities valuable in the current postindustrial society. This
type of digital divide has been identified between those who have the
necessary competences and skills to benefit from computer use and those
who do not. These competences and skills are closely linked to the persons’
economic, cultural and social capital (Pedró, 2009). That means that not
all types of Internet use and appropriation will empower young people
and help them build the capabilities required for their future development
and secure their position in the economy.
Even though the process of Internet dissemination has produced an
important generational gap, meaning that young people in general have
integrated this technology much more rapidly than older generations, the
next section’s data analysis will demonstrate how class advantage still plays
an important role here. Children and youngsters inherit their class
position also in terms of a differential access to equipment, contacts and
competences available for them, which marks a difference in their
approach to digital technology. This gap carries a risk of social
polarization and disintegration.
As mentioned above, countries of the LA region have put their hopes in
the public promotion of Internet access and use, using the public school
system as the strategic point of entry, in order to counterbalance the
inequalities produced by technology dissemination. These efforts can be
understood from Durkheim’s perspective on the role he assigned to the
state. According to his vision, the state was the great architect, constructor
and producer of society and its development, through the design of
rational and dynamic policies (Caputo, 1996). The state has a regulatory
function for the collective interests: fixing individuals’ rights (García
Raggio, 1998) and generating the adequate conditions for their
observance. The education system is the privileged tool the state has to
pursue equal opportunities for society’s new generations.
In this new globalized era the concern for social exclusion is not only
connected to the categories of economic exploitation and dominance, but
can also be analyzed from a cultural and subjective angle. The Internet
has helped to integrate the economy from a global perspective, expanding
the market’s needs and logic, but leaving a portion of the population with
a high risk of social exclusion (García Raggio, 1998). Durkheim’s concern
for social integration is, then, still very relevant.
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256 Daniela Trucco Horwitz
Society, through its organized secondary institutions, with an
overseeing role of the state, regulates individual interests and contributes
to the encouragement of a moral existence that promotes social
integration. From Durkheim’s perspective, the state’s function, especially
through the education system, is the construction of social values,
organizing society in a way that ensures fairness, that is, allowing each
member to be treated as he or she deserves, inhibiting unjust or
humiliating dependency, in the understanding that each person also
maintains obligations to the other members of society (Richter, 1960).
“The main purpose of state intervention is to free the individual from
whatever environmental disabilities may keep them from realizing their
potentialities” (Richter, 1960: p. 202). This view is consistent with the
efforts that LA states have been promoting through their public education
policies, to guarantee that no portion of the new generations will be
excluded from the acquisition of these critical digital skills, and the key
capital and cultural assets that are generated through ICT use. The
presentation of data about the digital divide in LA, in the third section of
this chapter, will analyze how successful they have been in reducing digital
inequalities and promoting social integration.
The process of Internet integration in the
Latin American context
Although still at a large distance from the more developed regions of the
world, LA countries have shown significant progress in the home
availability of digital technological equipment. Particularly in the last few
years, the increase in the acquisition of home computers has been
dramatic and it probably relates to technological progress and the
consequent reduction of costs (see Table 16.1). The progress in Internet
connection at the household level has been slower and it is probably
associated with the high connectivity costs that still persist in the region.
In any case, the growth in ICT penetration is significant: while at the
beginning of the decade the access to the Internet was practically nil, by
the end of the decade countries such as Brazil, Uruguay and Chile show
connectivity levels that reach almost a third of their population.
The digital gap between richer and poorer countries is however patent.
Plus, the digital gap between different socioeconomic groups within each
country is significant. While on average 65 percent of households that
belong to the richest income quintile have access to the Internet at home,
only 2 percent of the poorest households (first income quintile) do. In
general, studies show that despite this segmented access to technology,
children and young people are entering the world of technology in
greater numbers. In households with 12-to-19-year-olds, connectivity is
rising at a faster rate than in households that do not have members within
this age range (ECLAC, 2011). Figure 16.1 shows that in most countries
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The digital divide in the Latin American context 257
Table 16.1 Latin America and the Caribbean (selected countries): Percentage of
households with computer and Internet access (years 2000–2009)
Country
Argentina
Bolivia
(Plurination
State of)
Brazil
Chile
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Computer
—
22
—
—
—
—
—
—
—
—
Internet
—
9
—
—
—
—
—
—
—
—
Computer
—
7
7
—
—
12
—
17
—
—
Internet
—
—
—
—
—
4
—
3
—
—
35
Computer
—
13
14
15
16
19
22
27
31
Internet
—
9
10
11
12
14
17
20
24
27
Computer
18
—
—
25
—
—
33
—
—
42
8
—
—
13
—
—
19
—
—
29
23
Internet
Colombia
Costa Rica
Computer
—
—
—
11
12
15
16
15
23
Internet
—
—
—
5
6
6
7
7
13
15
Computer
14
17
20
—
24
27
28
31
34
37
Internet
Ecuador
El Salvador
Guatemala
4
5
7
—
—
10
10
12
15
18
Computer
—
—
—
18
—
—
18
—
23
23
Internet
—
—
—
4
—
—
2
—
7
8
12
Computer
3
5
5
5
6
7
8
9
11
Internet
1
2
2
2
2
2
2
3
4
6
Computer
4
—
—
—
—
—
11
—
—
—
—
Internet
Honduras
Mexico
Nicaragua
Panama
Paraguay
1
—
—
—
—
—
2
—
—
Computer
—
—
—
5
5
6
8
10
—
—
Internet
—
—
—
—
1
2
1
2
4
—
Computer
—
12
15
—
18
19
21
22
26
27
Internet
—
6
7
—
9
9
10
12
14
18
Computer
—
2
—
—
—
4
6
—
—
7
Internet
—
—
—
—
—
0
0
—
—
2
Computer
—
—
—
—
—
—
16
17
—
—
Internet
—
—
—
—
—
—
8
9
12
—
5
—
5
6
6
9
9
11
15
19
Computer
Internet
Peru
1
—
1
2
1
2
3
3
6
11
Computer
—
5
6
7
7
8
9
14
16
19
Internet
—
0
1
1
1
2
3
6
7
10
Dominican
Republic
Computer
—
—
—
—
—
—
—
—
—
17
Internet
—
—
—
—
—
3
—
5
—
—
Uruguay
Computer
—
18
18
19
21
22
24
28
39
48
Internet
—
13
14
14
13
13
13
16
23
28
Venezuela
(Bolivarian
Republic of)
Computer
—
—
—
10
10
10
—
15
17
—
Internet
—
—
—
2
2
2
—
6
9
—
Source: Author’s preparation based on ECLAC special tabulations of household surveys
data, harmonized by OSILAC ICT Statistical Information System.
The Digital Divide_BOOK.indb 257
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258 Daniela Trucco Horwitz
(particularly those with more advanced levels of access), the access to the
Internet is higher in households with a presence of school aged youth,
which is the generation that supposedly represents the window of
opportunity for these countries to enter the information society well
prepared. The younger generation might be pushing the acquisition of
this type of equipment at home, accelerating market penetration.
However promising the progress of Internet access within the younger
generations might seem, a less optimistic approach is reached once these
advances are analyzed by class position. Younger generations from
privileged social classes are the social group that has advanced most
rapidly in the home acquisition of Internet connectivity. The burgeoning,
market-driven penetration of ICT in the region is creating substantial gaps
in access to equipment by social class (ECLAC, 2011). While approximately
7 percent of 12 to 19-year-olds that have access to the Internet at home
belong to the highest income quintile, only 1 percent of this population
belong to the poorest income quintile (Figure 16.2). The regional average
however, hides the heterogeneity among LA countries and their respective
living standards. Less affluent countries such as Honduras and Bolivia
have fewer class differences in access to ICT, because households of the
higher income quintiles have much lower living standards than those of
more affluent countries, such as Brazil, Chile or Uruguay, which show a
clearer class divide in household ICT access.
40%
35%
Yes = households with members 12 to 19 years old
30%
No = households without member 12 to 19 years old
25%
20%
15%
10%
0%
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
5%
y
la
le
ia
il
ay eru
bia R ica dor ador nada uras xico ama
ua
liv
ue
az Chi
P
gu
d
Br
Bo
lom ta Ecua
rug enez
Me Pan ara
alv G ra
on
U
S
Co Cos
H
P
V
El
Figure 16.1 Latin America and Caribbean (LAC) (15 countries): Percentage of
households with Internet access, with or without members between 12
and 19 years old (around 2009)
Source: Author’s preparation based on ECLAC special tabulations of data from household
surveys.
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The digital divide in the Latin American context 259
40%
35%
7%
30%
25%
10%
10%
5th quintile
20%
4th quintile
15%
3rd quintile
8%
7%
10%
4% 5% 6%
5%
7%
7%
2nd quintile
1st quintile
LAC 2008-2009
Chile 2009
Uruguay 2009
Brazil 2009
Costa Rica 2009
Colombia 2009
Paraguay 2009
Peru 2009
Panama 2007
Venezuela 2008
Ecuador 2009
El Salvador 2008
Bolivia 2007
Honduras 2007
3%
4%
4% 3%
2% 2%
1%
0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 1%
Figure 16.2 Latin America (13 countries): Percentage of people 12 to 19 years old
that have Internet at home, according to country and household
income (around 2009)
Source: Author’s preparation based on ECLAC special tabulations of data from household
surveys.
Identifying different connectivity access rates by generation leads to an
examination of how much this weakens or reinforces class-based gaps
(Kaztman, 2010). A look at the figures shows that in the countries where
technology is more market-driven (such as Brazil, Chile and Uruguay) the
class gaps for younger-generation users are not narrowing (ECLAC, 2011).
They are widening (see Figure 16.3). In households without young people
the gap is less than 40 percentage points, while in households with young
members in the more connected countries, the gap has grown to over 50
percent.
The digital divide in LA is, in part, rooted in unequal access stemming
from enormous differences in the availability of equipment. But it also has
to do with the way students use and can benefit from such equipment. At
this other level, inequality is evidenced in different levels of ability to use
ICT productively and take advantage of their potential for developing the
competencies and skills necessary for integration in the globalized world
(Sunkel and Trucco, 2010).
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260 Daniela Trucco Horwitz
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
Households with 13 to 19 year olds
Uruguay 2009
Brazil 2008
Chile 2006
Costa Rica 2008
Mexico 2007
Peru 2009
Panama 2007
Ecuador 2009
Paraguay 2009
El Salvador 2008
Honduras 2007
0.0
Nicaragua 2006
10.0
Households with members over 20
Figure 16.3 L A (11 countries): Difference in the proportion of households with
Internet connection in the highest and lowest income quintiles by
presence or absence of household members aged 13–19, around 2008a
(percentages)
Source: ECLAC (2011), on the basis of special processing of household surveys reconciled
by OSILAC; and Kaztman (2010).
Countries shown in order of the percentage of households with Internet connection in
each country.
a
Data collected through international educational assessment tests like the
OECD PISA (OECD, 2009) show the class differences between secondary
students in terms of Internet and computer use. An optional student
questionnaire is offered in the PISA measurement that allows a deeper
analysis in relation to student use of ICT at school. Only four countries of
the Latin America and Caribbean (LAC) region chose to participate in
this additional component: Chile, Panama, Trinidad and Tobago, and
Uruguay.
The main uses that young people make of computers involve the
Internet, primarily as a means of communication and, to a lesser degree,
to download music and games. But in these four countries, homework use
of the computer and the Internet at home is the most relevant use in terms
of frequency, even higher than the OECD countries’ average.
Considering the high frequency users for these different areas and the
students’ class position, the second type of digital gap discussed before
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The digital divide in the Latin American context 261
becomes evident. Class advantage in terms of taking full advantage of
the Internet’s potential in a broad sense is clear, which means that
youngsters that are born in a more advantageous socioeconomic
situation also acquire better skills and competences to participate as
adults in society. OECD PISA 2009 reveals that approximately 20 to 25
percent of 15-year-old students are frequent users for schoolwork related
activities (see Figure 16.4).
A striking difference between the LAC countries and the OECD
countries is the distribution of these frequent scholar ICT users. While in
OECD countries they are distributed almost in equal portions according
to the students’ economic and sociocultural quartiles, 2 LA countries show
a clear digital gap according to class position. Most frequent users belong
to the third and fourth superior quartiles, while very few belong to the first
one. The same tendencies can be observed from the data related to
communicational and recreational Internet use. These are the most
30%
Percentage of students
25%
10%
9%
14%
20%
6%
15%
7%
9%
10%
5%
Chile
4%
4%
2%
2%
5%
Low-middle Quartile
Inferior Quartile
6%
6%
3%
0%
Middle Quartile
8%
8%
Superior Quartile
5%
5%
3%
Panama Trinidad & Uruguay
Tobago
5%
OECD
Figure 16.4 Percentage of 15 year old students that are high frequency users of ICT
for school work at home, according to their economic and sociocultural status, year 2009
Source: Author’s preparation, based on ECLAC’s special tabulations of PISA 2009 ICT
Questionnaire data.
Note: OECD represents the weighted average of OECD countries. High frequency users
were defined through a summation index of students who declare to use ICT at least once a
week for the following activities: Doing homework on the computer; browse the Internet for
schoolwork; use e-mail for communication with other students about schoolwork; use e-mail
for communication with teachers and submission of homework or other schoolwork;
download, upload or browse material from your school’s website; and check the school’s
website for announcements.
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262 Daniela Trucco Horwitz
common and natural ways for young people to approach these
technologies, but class position which already generates a gap in access to
the equipment, also generates a gap in terms of the use and skill
development associated with it.
In general, the digital divide in LA has been understood only in terms
of access to technology. Yet, as the discussion of user profiles has shown, a
more profound digital gap has also emerged between those who have the
social, cultural and economic position needed to take advantage of
computers, and, in addition, have access to the Internet at home, and those
who occupy a less favorable position in society. As happened with
educational attainment differentials, there is a risk that strongly marketbased advantages for families will continue to be the prime determinant of
digital divides (ECLAC, 2011, p. 108).
The role of the state in the regulation of the market’s
divergent tendencies
Many countries in the region have made significant progress in recent
years in integrating ICT into the education sector. Most of the schools in
this region are part of a public education system. As part of that process,
many countries have implemented policies involving the creation of
institutions and the allocation of significant resources. As mentioned
above, a central thrust of the efforts in the region to deploy public policies
in the area of ICT for education has been to contribute to social
integration and to avoid the social polarization that would result if broad
segments of the population were denied access to the new opportunities
offered by ICT (Sunkel and Trucco, 2010).
As Durkheim would have asserted, the state in LA countries should be
playing a regulating role to diminish the market’s divergent tendencies, in
order to protect and include those individuals who are being left behind.
Schools have been seen as strategic playing fields for reducing inequalities
of access. However, if these programs in the schools are to contribute to
equity, then merely reducing inequalities of access is not enough. What is
needed is to ensure that ICT for education can prevent the gap in skills
and behaviors among Internet users from exacerbating existing
differences. The discussion that follows uses the data provided by the PISA
studies to analyze how effective the state has been in achieving both
objectives through its education policies in LA countries.
As Table 16.2 shows, the percentage of 15-year-old students with school
access to computers has increased significantly in the LA countries that
have participated in the PISA assessments. Computer coverage at schools
has reached high levels, closer than household computer access to the
average coverage reached in more developed regions of the world, such as
the OECD countries. Moreover, contrary to the tendencies followed by
household ICT access, schools’ computer access shows a more equitable
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The digital divide in the Latin American context 263
growth in coverage, reducing by half the social gap between students of
different social backgrounds in the last decade (from 19 to 8 percentage
points) (Claro et al., 2011).
Table 16.2 Latin America (7 countries) and OECD average: Percentage of 15-yearold students with computer access in school, according to ESCS
quartiles (years 2000 to 2009)
Inferior Quartile (%) Superior Quartile (%) Class Gap (%)
Argentina
Brazil
Chile
Colombia
Mexico
Peru
Uruguay
LA
OECD
2000
48
67
20
2006
83
95
13
2009
80
95
15
2000
50
70
20
2003
37
78
41
2006
67
89
23
2009
89
95
6
2000
97
100
3
2006
92
98
6
2009
100
100
0
2006
89
94
5
2009
98
99
1
2000
56
83
27
2003
61
87
27
2006
89
96
7
2009
90
98
8
2000
38
66
29
2009
71
95
25
2003
75
86
10
2006
88
91
3
2009
100
100
0
2000
54
73
19
2003
47
81
34
2006
79
93
14
2009
88
96
8
2000
82
85
3
2003
75
85
10
2006
90
90
0
2009
98
100
2
Source: Author’s preparation, based on ECLAC’s special tabulations of PISA 2000, 2003,
2006 and 2009 data.
Note: LA and OECD represent the weighted average of each regions participating
countries.
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264 Daniela Trucco Horwitz
Internet school access has followed a similar tendency but at a lower rate,
both in terms of reaching a lower percentage of schools and in terms of
reducing social gaps at a lower rate (Claro et al., 2011). Nevertheless,
equitable growth coverage has been an important policy contribution that
is also reflected in the real opportunity to use a computer at school, when
looking at the student computer ratio data (see Table 16.3).
Table 16.3 shows that the gap between student to computer ratio in
school for students of different social background has decreased
significantly in most LA countries over the last few years. The distance
between the two extreme economic and sociocultural quartiles has
declined from a difference of 39 students in the year 2000 to a difference
of 7 students per computer available in school in the year 2009.
The sum of these ICT access indicators in the school system shows that
education policy has had significant results in terms of promoting broad
Table 16.3 Latin America (9 countries) and OECD average: Student to computer
ratio at school, according to ESCS quartiles (years 2000 to 2009)
Inferior Quartile Superior Quartile
(%)
(%)
Argentina
Class Gap
(%)
2000
58
32
2009
34
18
26
17
Brazil
2000
218
42
177
2009
45
28
18
Chile
2000
46
37
9
2009
20
22
–2
Colombia
2009
38
26
13
Mexico
2000
37
16
21
2009
13
10
3
Panama
2009
20
21
–1
Peru
2000
86
38
48
2009
24
13
11
Trinidad & Tobago
2009
15
16
–1
Uruguay
2000
31
27
3
2009
25
21
4
LA
2000
72
33
39
2009
24
17
7
OECD
2000
11
10
1
2009
8
7
1
Source: Claro et al. (2011), based on ECLAC’s special tabulations of PISA 2000–2009 data.
Note: LA and OECD represent the weighted average of each region’s participating
countries. Uruguay’s 2000 data is from the 2003 PISA.
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The digital divide in the Latin American context 265
access to ICT infrastructure and equipment. Moreover, these efforts have
benefited the least favored socioeconomic sectors, reducing the distance
that separated them from the more privileged sectors. However, these
indicators show that there is still a long path to advance in terms of
having access that allows real quality and regular use of ICT for students
in school.
The data obtained through the PISA ICT special questionnaire (only
applied in four countries of the LA region) demonstrate that the
percentage of students that are high frequency users of computers and the
Internet at school is generally lower than the percentage of high frequency
users at home for the same type of activities. For example, on average 69
percent of students from these four LA countries use the computer at
home at least once a week for homework, compared to 42 percent that do
so at school. Another example is chatting online, one of the most
widespread activities: while on average 65 percent of LA students chat at
least once a week from a home computer, only 10 percent do so from a
school computer.
The problem with access opportunities at schools or other places such
as commercial establishments is the low intensity at which individuals can
make use of the technology. Because of the cost, or due to access
conditions at educational institutions, those who use these locations
normally do so for shorter periods of time and thus have fewer possibilities
for developing digital competencies for social and productive integration
than do young people who can access the Internet at home (ECLAC, 2011).
However low this percentage of high frequency school ICT users might
be, it is worthwhile analyzing what user profiles have been developed in
this context and the role of the school system in generating or reducing
social gaps at this level. Despite ICT access differences between LA
countries and OECD countries, when analyzing user profiles, you find
similar patterns of use. Moreover, LA countries show a higher percentage
of ICT high frequency users at school (see Figure 16.5).
Moreover, what appears as a relevant difference in the regional user
profiles is the prominent place that schoolwork ICT use has in LA
countries, as compared to the OECD average. For example (see Figure
16.5), in Chile 45 percent of students are high frequency users of school
Internet for schoolwork, compared to only 31 percent in OECD countries.
On the other hand, both Chile and Panama have more than 30 percent of
their students using school computers at least once a week for their
individual homework, while in OECD countries this rate drops to 14
percent. These results are important, because they might be revealing a
certain pedagogical orientation from teachers or even parents, to promote
the use of ICT in support of schoolwork. This would constitute a base for
what could be an interesting projection of the development of relevant and
more complex skills related to ICT (Claro et al., 2011), reinforcing
Durkheim’s perspective.
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266 Daniela Trucco Horwitz
Browse the Internet for schoolwork
45%
Chat
Doing individual homework
on a school computer
31%
14%
Doing group work and
communication with other students
Use email
Chile
Panama
OECD
Figure 16.5 Chile, Panama & OECD average: percentage of 15 year old students
who declare using school computers at least once a week, according to
type of activity (year 2009)
Source: Claro, et al. (2011), based on ECLAC’s special tabulations of PISA 2009 data – ICT
questionnaire.
Note: OECD represents the weighted average of the region’s participating countries.
Now, in terms of socioeconomic gaps, despite the lower possibilities of
having high frequency ICT users at school, the difference in the
percentage of students following this pattern of use is slightly more
favorable to students that belong to less benefited social backgrounds.
Figure 16.6 shows the patterns of school use for students of the four LA
countries, distinguishing between those students that belong to the
superior and inferior economic and sociocultural status quartiles. That
means that schools have been able to provide equal opportunities of
meaningful educational uses of technology at school, independent of the
students’ social background.
In today’s increasingly global economy, the Internet and the skills
developed through and with them are more and more relevant for
Durkheim’s concern for social integration. The analysis has shown that LA
states have used education policy as one of their main strategies in
promoting this integration process, and this approach has been relatively
successful in terms of both providing access and promoting meaningful
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The digital divide in the Latin American context 267
Browse the Internet for schoolwork
15%
10%
5%
Chat
Doing individual
homework on a
school computer
0%
Use email
Inferior Quartile
Superior Quartile
Figure 16.6 Latin America (4 countries): percentage of 15 year old students that
use ICT at least once a week in school, by type of activity and the
student’s economic and socio-cultural status (year 2009)
Source: Claro, et al. (2011), based on ECLAC’s special tabulations of PISA 2009 data – ICT
questionnaire.
Note: LAC represents the weighted average of Chile, Panama, Trinidad & Tobago and
Uruguay.
use to the new generations. However, the efforts must be greater in order
to compensate for the huge differences generated through social class and
household opportunities.
Summary and conclusions
The ongoing technological revolution advances and redefines the world’s
opportunities for development, for individuals and society in general. ICT
dissemination is fast and moves almost in an automatic way pushed by
market forces. LA has not been excluded from this process. However, the
market-driven forces tend to leave some social sectors behind and to
reproduce pre-existing social inequities (with the risk of exacerbating
some of them) between and within nations. The great risk is an increase in
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268 Daniela Trucco Horwitz
social polarization, leaving social groups completely excluded from the
possibility of integrating with the knowledge society. Social disintegration
was one of Durkheim’s main apprehensions in relation to the
modernization process of his time.
That also seems to be the case up until now with regards to household
acquisition of ICT equipment and the opportunities provided of use and
competence development for younger generations. Greater intensity and
productivity in use requires more time in front of monitors and quality
programs for developing the required skills set. Here, the difference
between those who access these technologies at home and those who do
not currently determines the depth of the digital divide and reinforces
underlying socioeconomic and capital gaps (ECLAC, 2011: p. 109).
As Durkheim would have seen it, the risks of social disintegration
compel the state to play a role in counteracting these inequalities by
offering more and better access to technology to those who have none at
home, deepening penetration in order to increase usage time. ICT for
education constitutes, following Durkheim’s conception, one of the
essential intellectual assets that the state should guarantee for all society’s
members. It has become a basic skill required to participate in today’s
economy, social networks and political arena both at the national and
international levels.
Education policy and the school system have been a positive point of
entry in the LA region. Especially in terms of providing more equitable
access to technology but also in terms of offering pedagogical guidance
that motivates students to use the technology autonomously both for
research and homework. However, there still is much to be done in terms
of promoting an equitable formation of knowledge and cultural assets.
The school system is still far from providing a similar opportunity for ICT
utilization to the one obtained through home access. School systems in LA
countries have great challenges in terms of effectively integrating digital
skills in the curriculum and promoting frequent and significant uses that
will provide new generations with the required skills to compete and
participate in the opportunities offered by society. This analysis shows how
Durkheim’s theoretical perspective, developed a century ago to
understand Europe’s modernization process, still has strength and
analytical value. His reinterpretation enlightens the comprehension of the
social consequences brought by technological changes. The velocity of
these urgently demand the need for sociological reflection for which a new
reading of Durkheim’s papers can prove valuable.
References
Caputo, L. (1996). Durkheim, algunos elementos para la comprensión de las
organizaciones sociales y los cambios en América Latina. Asunción, Paraguay:
BASE Investigaciones Sociales.
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The digital divide in the Latin American context 269
Claro, M., Espejo, A., Jara, I. and Trucco, D. (2011). Aporte del Sistema Educativo a la
Reducción de las Brechas Digitales. Una mirada desde las mediciones PISA. Santiago,
Chile: ECLAC, forthcoming.
ECLAC (Economic Commission for Latin America and the Caribbean) (2011).
Social panorama of Latin America, 2010 (LC/G.2481-P). Santiago, Chile: United
Nations publication.
García Raggio, A. (1998). Transitando por los márgenes: las transformaciones del trabajo
y el debilitamiento de la ciudadanía. In E. De Ipola, (ed.) La Crisis del Lazo Social.
Durkheim, cien años después. Buenos Aires, Argentina: Editorial Universitaria.
Kaztman, R. (2010). Impacto social de la incorporación de las TIC en el sistema educativo,
(LC/L.3254-P), Santiago, Chile: Serie de Políticas Sociales 166, ECLAC.
OECD. (2009). Pisa 2009 – Organisation for Economic Co-operation and Development.
Retrieved from http://www.oecd.org/pisa/pisaproducts/pisa2009
Pedró, F. (2009). Are the New Millennium learners making their grades? Technology use
and educational performance in PISA. Paris: OECD Centre for Educational
Research and Innovation (CERI).
Richter, M. (1960). Durkheim´s politics and political theory. In K. Wolff (ed.) Essays on
sociology and philosophy by Emile Durkheim et al. with appraisals of his life and thought.
Columbus, OH, US: Ohio State University Press.
Sunkel, G. and Trucco, D. (2010). New information and communication technologies for
education in Latin America: Risks and opportunities. (LC/L.3266-P). Santiago,
Chile: Serie de Políticas Sociales 167, ECLAC.
UNDP (United Nations Development Programme). (2006). Desarrollo humano en
Chile. Las nuevas tecnologías: ¿Un salto al futuro? Santiago, Chile: United Nations.
Usátegui, E. (2003). La educación en Durkheim: ¿Socialización versus conflicto? Revista
Complutense de Educación, 14(1), 175–194.
Notes
1 Most of the information and data analysis included in this chapter was
developed in the context of a project carried out by the United Nations ECLAC
– Alliance for the Information Society, phase 2 – which is financed by the
European Union. The author is grateful for the valuable statistical support
provided by Andrés Espejo.
2 As measured by the ESCS which refers to the Economic, Social and Cultural
Status. This index is elaborated based on the following variables: International
Socio-Economic Index of Occupational Status (ISEI); parents’ highest level of
education converted into school years; PISA’s family richness index; PISA’s
educational resources index; and PISA’s index related to classic cultural
possessions at home (http://stats.oecd.org/glossary/detail.asp?ID=5401).
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17 The Central Asian
digital divide
Barney Warf
University of Kansas
The digital divide, or social and spatial differentials in Internet access, has
been the subject of a growing body of literature (Norris, 2001; Korupp and
Szydlik, 2005; Warf, 2001), revealing how digital communications are
enfolded in relations of wealth and power in ways that reproduce real world
inequalities in virtual space. A significant literature has illustrated how the
Internet is entwined with social inequalities (e.g., Witte and Mannon, 2010),
and, by enforcing the information asymmetry advantage of those with
access, may enhance social and spatial differences within societies. An
enormous body of classical and more contemporary social theory has
sketched the drivers and manifestations of social and spatial inequality, and
need not be recapitulated here; suffice it to say that the literature on the
digital divide has both been inspired by such theorizations and in turn
traced how inequalities are manifested in terms of class, gender, and ethnic
differences in Internet access (Compaine, 2001; Cooper and Compaine,
2001; Crang, Crosbie and Graham, 2006; Stevens, 2006). “Access” and “use”
are vague terms, but are generally taken to mean deployment of the Internet
at home or at work; rather than a simple access/non-access dichotomy, it is
more useful to think of a gradation of levels of access, although data of this
subtlety do not exist. For Marxists, the digital divide is yet another dimension
of class inequality; for feminists, it is evidence of patriarchal limitations on
women’s opportunities; and for theorists who take ethnicity as their point of
departure, the “racial ravine” constitutes another means by which minorities
suffer from discrimination.
Despite its historical status as the crossroads of Asia, Central Asia has
been peripheralized in studies of the Internet (but see Warf, 2010). This
oversight may be attributable largely due to the region’s marginal
geopolitical status during the Cold War, the crippling legacy of Soviet
political and economic policies, its relatively small population size and low
Internet penetration rates, and its persistent poverty and endemic
government corruption.
The Internet in Central Asia affords the opportunity to study
international technology diffusion and adoption, including the incentives,
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The Central Asian digital divide 271
policies, and barriers that shape the uneven growth of users over time and
space (Caselli and Coleman, 2001; Clarke, 2004; Comin and Hobijn, 2004;
Keller, 2004). The view that the diffusion of the Internet is a relatively
straightforward matter of removing economic obstacles and encouraging
adoption hints at technical solutions for complex social and political
problems. This approach to overcoming the digital divide is redolent of
older modernizationist approaches to development that portray
technology adoption as a simple, linear path. Yet the digital divide in
Central Asia reveals a far more complex situation, one in which political
dynamics play a fundamental role in shaping who has Internet access and
who does not, including frequently corrupt and oppressive governments.
Indeed, Central Asia reflects mounting inequalities characteristic of
neoliberalized societies worldwide, with a small, wealthy, globalized elite
and large numbers of impoverished and marginalized residents (Anderson
and Pomfret, 2004; Falkingham, 2005). In this light, as it emerged from
the relative inequality of the Soviet era into the globalized, privatized
world of neoliberalism, the region began to offer a unique laboratory in
which to examine how social and spatial discrepancies are reproduced and
sustained, a topic that falls squarely within conventional theorizations of
inequality. This chapter examines several dimensions of the Central Asian
digital divide. It begins with an overview of the broad contours that shape
social and spatial inequalities in the region, including incomes and
poverty, the incipient fiber optic network, satellite services, government
policies, and the slow arrival of broadband. Second, it focuses on the
number and distribution of Central Asian netizens, the rapid growth of
the Internet in the region, and the role played by cybercafés; it also points
to the urban biases in Internet use, male dominance, and touches on some
of the cultural obstacles to participation online. The third part reviews
Internet censorship in the region in light of many states’ attempts to
restrict cyber-activism, a point raised to emphasize the politics of the
digital divide. The conclusion highlights the chapter’s principal analytical
findings.
The architecture of the Central Asian digital divide:
Infrastructures and policies
Central Asian countries vary widely in terms of incomes and standards of
living (Table 17.1), ranging from miserably poor Afghanistan ($US 900
GDP per capita annually) to $12,700 in Kazakhstan. With the exception of
Afghanistan, where a little more than one-quarter of the population can
read or write, these countries have achieved almost universal literacy, in
part due to the legacy of the Soviet Union. However, most have significant
pools of people living below the poverty line, including more than half the
population of Tajikistan. Because digital divides the world over are closely
correlated with incomes, the existence of millions of impoverished people
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272 Barney Warf
is a significant obstacle to the implementation of equal access to
cyberspace. In many countries, landline telephone systems, which are
critical for dial-up access, are antiquated and in disrepair, leading to slow
upload and download speeds. Such communications networks still rely
heavily on copper cable wires, when most of the world’s
telecommunications traffic has moved decisively into fiber optic cable.
Mobile or cell phone penetration rates are much higher, but vary widely,
from 22.5 percent in Turkmenistan to 96 percent in Kazakhstan.
Other than the telephone network, fiber optics and satellites remain
the dominant technologies facilitating Internet access, especially for the
increasingly important broadband applications. In Central Asia, the
principal fiber optic line is the 27,000 km-long Trans-Asia-Europe (TAE)
cable, the world’s longest overland route, which began operations in 1998.
It begins in Frankfurt, extends to Turkey, crosses Iran, has trunk lines
northward to Georgia, Armenia, and Ukraine, and follows the ancient Silk
Road route into western China and hence to Shanghai (Figure 17.1). Built
by a consortium of international telecommunications companies, it
constitutes the major high-capacity line within the region. However, while
much of the world has witnessed a glut in fiber capacity, in Central Asia
fiber connections remain relatively scarce and thus expensive. Some
countries, such as Uzbekistan, have a reasonably well developed fiber
infrastructure, complemented with microwave radio relay links, while
others, such as Kyrgyzstan, are almost bereft of fiber and must utilize other
modalities.
Satellite Internet provides another opportunity for providing access
where terrestrial connections are not viable or are prohibitively expensive,
and many Central Asian Internet service providers (ISPs) rely on satellite
Table 17.1 Central Asian economic, literacy, and ITC statistics, 2011
GDP per
% below
capita (PPP) poverty line
($US)
Adult literacy Telephone
Mobile phone
rate
landlines per penetration
1000 people
Afghanistan
900
36.0
28.1
0.4
29.0
Kazakhstan
12,700
8.2
99.5
24.0
96.0
Kyrgyzstan
2,200
40.0
98.7
9.1
62.7
Mongolia
3,600
36.1
97.8
7.0
66.8
Tajikistan
2,000
53.0
99.5
4.2
53.7
Turkmenistan
7,500
30.0
98.8
0.3
22.5
Uzbekistan
3,100
26.0
99.3
6.8
44.5
Source: CIA World Factbook; International Telecommunications Union.
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The Central Asian digital divide 273
Figure 17.1 The Trans-Asia-Europe (TAE) fiber optics cable.
Source: redrawn from http://www.science-arts.org/Internet/node37.html
services. International satellite services such as Intelsat, Eutelsat, and
AsiaSat offer services to Central Asian ISPs. Some governments in the
region have taken steps in this direction. For example, in 2006, Kazakhstan
launched its own satellite, KazSat, followed by a second in 2009, which
lowered the costs of satellite telecommunication services. Private satellite
ISPs also serve various Central Asian countries. Such providers include
Bentley Walker, with three satellites hovering over the central Eurasian
landmass, and GT&T’s SkyOne, which offers broadband connections.
Other trans-national satellite ISPs include IDM International, Satcom,
Skyvision, BusinessCom, and the French firm e-Quai.
In addition to the Internet’s infrastructure, government telecommunications policies are important in shaping the contours of
Internet access in Central Asia. The neoliberal logic that celebrates
markets held that deregulation and privatization would encourage
competition, innovation, and risk-taking, lower prices, and improve service
quality. Empirically, countries that deregulated their telecommunications
markets have tended to have more competition, higher penetration rates,
and lower user prices than those that did not. In Central Asia, privatization
and deregulation have occurred much more slowly than in most of the
world, and are often handicapped by governments fearful of losing control
over a vital means of information control. In 2007, the Kazakh operator
Kazakhtelecom was the region’s first state-owned company to actually
offer its shares for sale, but only 4.1 percent have been sold. The Kyrgyz
government has gradually liberalized its telecommunications sector, which
improved the affordability of Internet access there and made use of
cyberspace more attractive and profitable; however, as OpenNet Initiative
(2010a) points out, “Kyrgyzstan is an effectively cyber-locked country
dependent on purchasing bandwidth from Kazakhstan and Russia.” The
privatization of the Tajik operator Tochiktelecom began in 2003, but has
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274 Barney Warf
not advanced much since then. Mongolia has partially privatized Mongol
Telecom. Some governments cling to the older model of state-owned
telecommunications, such as Afghanistan and Uzbekistan, in which
UzbekTelecom retains a legal monopoly status even as it is being privatized.
In 2001, following a brief window of privatization that opened with
independence in 1991, Turkmenistan granted a monopoly over data
services to TurkmenTelecom, driving several smaller ISPs out of business.
In such cases, service tends to be poor and prices for dial-up and ISPs are
relatively high and certainly out of reach for low income residents.
The number of ISPs varies among Central Asian countries (Table 17.2),
ranging in 2008 from 1 in Turkmenistan to 859 in Uzbekistan. These
numbers reflect not only varying levels of demand for Internet services
and penetration rates, but also the degree to which governments
encourage, tolerate, or facilitate competition in this sector. Many ISPs in
the region lack international connections and must purchase bandwidth
from top-tier national providers. Some ISPs have introduced Internet
cards, which have become very popular in cybercafés.
Most Central Asian netizens must rely on dial-up connections, which
can be frustratingly slow in an era in which graphical material has become
common on the Internet. Broadband, the latest frontier of the digital
divide the world over, remains poorly developed in Central Asia. There are
enormous variations among Central Asian countries in the availability and
cost of broadband services (Table 17.3). The ratio of broadband subscribers
per 1,000 people ranged from essentially zero in Tajikistan and
Turkmenistan to almost 76 percent in Kazakhstan. These discrepancies
can be explained in part by varying national levels of investment in fiber
cables. Kazakhtelecom, for example, has invested in a national data
transfer system that has reduced transmission prices significantly (ESCAP,
2009). Moreover, the region’s telecommunications providers charge vastly
different prices for domestic broadband service, ranging from relatively
Table 17.2 Number of Internet service providers in Central Asian countries, 2008
Afghanistan
46
Kazakhstan
105
Kyrgyzstan
38
Mongolia
14
Tajikistan
10
Turkmenistan
Uzbekistan
1
859
Source: OpenNet Initiative.
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The Central Asian digital divide 275
Table 17.3 Central Asian domestic broadband subscriptions and costs, 2009
Broadband subscribers per
1,000 people
Broadband subscription tariff
($US/month)
Kazakhstan
75.9
17.2
Kyrgyzstan
0.9
48.1
Mongolia
1.8
8.5
Tajikistan
0
Turkmenistan
—
—
Uzbekistan
9.9
199.5
363.6
Source: World Bank, 2011.
low costs in Mongolia and Kazakhstan to Tajikistan’s exorbitant fee of $US
363/month, which effectively, and not surprisingly, puts broadband
financially out of reach for almost all of the country’s residents.
The enormous popularity of mobile or cellular phones is often heralded
as a means to overcome the digital divide, especially in developing
countries. In Kyrgyzstan, 21 percent of netizens access the Internet using
mobile devices (OpenNet Initiative, 2010a). The region also exemplifies
the potential of “leap-frogging” old technologies: the Kyrgyz ISP AsiaInfo
recently initiated Central Asia’s first wireless broadband service in Bishkek.
The Afghani government recently contracted with two Chinese firms to
build a national wireless network. In Kazakhstan and Mongolia, wireless
technologies now allow for the rise of yurt-based Internet access (Davison
et al., 2003). However, because most Internet users who access the web via
wireless means are already connected, it is unlikely that increasing use of
mobile phones and the mobile Internet access they provide will have
significant impacts on the Central Asian digital divide.
Central Asian netizens
Data on Internet users for March 2011 were drawn from Internet World
Users Statistics (www.Internetworldstats.com); unfortunately, they do not
include information on the socio-demographic characteristics of users or
their location within countries. As Table 17.4 reveals, the distribution of
Internet users among the seven countries included in this analysis varies
widely. In total, there were more than 17.7 million Central Asian netizens
in December 2011; by far the largest populations of users were found in
Uzbekistan (7.5 million) and Kazakhstan (5.5 million). However, like many
developing regions in the world, Central Asia has witnessed astronomical
rates of growth in Internet access: between 2000 and the end of 2011, the
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276 Barney Warf
Table 17.4 Central Asian Internet users and penetration rates
Total users (000s)
%
Internet
Growth Penetration
Rate 12/2011
Facebook
Subscibers
(000s)
2000
12/2011
Afghanistan
1.0
1,256
125,500
4.2
198.0
Kazakhstan
70.0
5,449
7,471
35.1
293.0
Kyrgyzstan
51.6
2,194
4,152
39.3
49.8
Mongolia
30.0
355
1,067
11.3
182.6
Tajikistan
2.0
795
34,900
10.4
20.3
Turkmenistan
2.0
80
3,900
2.0
13.0
Uzbekistan
7.5
7,550
100,567
26.8
82.9
Source: http://www.internetworldstats.com
number of users in the region jumped by almost 10,700 percent, more
than 50 percent annually. Indeed, the Internet is arguably the fastest
diffusing technology in world history. Penetration rates in the region
varied widely: some, such as Kyrgyzstan (39.3 percent) and Kazakhstan
(35.1 percent) are above the world average of 30.0 percent, whereas in
others, such as Afghanistan (4.2 percent), the Internet is a marginal
presence at best, or in the case of Turkmenistan (2.0 percent), almost
completely absent. Finally, the popularity of Facebook in the region should
be noted, with 839,600 people using this popular social networking site
(4.7 percent of the region’s Internet users).
In a part of the world that does not enjoy particularly high incomes or
standards of living, Internet access can be prohibitively expensive. Kapitsa
(2008, p. 45), for example, notes that:
in Kazakhstan, the unlimited dial-up Internet connection package
offered by Kazakhtelecom cost about €86 per month, the unlimited
ADSL connection – from €102.45 (at 64 Kbps) to €3278.57 (at 2048
Kbps) per month, and the unlimited cable Internet connection – from
€9,163.09 (at 3 Mbps) to €24,432 (at 10 Mbps) per month. Taking into
consideration that the average monthly salary in Kazakhstan was 292
euros (as of January 2007), it is not surprising that most of Internet
users have been accessing the Internet at their workplaces.
Personal computer ownership rates are relatively low in Central Asia (e.g.,
two per 100 people in Kyrgyzstan in 2009, one in Tajikistan and
Uzbekistan).
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The Central Asian digital divide 277
Because of low rates of computer ownership, and because ISP access
charges are often high, many users rely upon privately-owned Internet
cafés for access rather than individual accounts. Cafés are particularly
important for those who lack dial-up access at home or at work or who
simply cannot afford personal computers of their own. In Kyrgyzstan, for
example, the majority of Internet users depend on cafés (Privacy
International, 2003; Srinivasan and Fish, 2009). In Uzbekistan, roughly
40 percent of users do so from their homes, 40 percent use their place of
work, but 30 percent use cybercafés (OpenNet Initiative, 2010c). In
Kazakhstan, half of users have Internet access from their homes. In
Afghanistan, cybercafés are essentially confined to the airport in Kabul
and a few luxury hotels. In Tajikistan, there is a network of 400 cafés
which are the dominant points of entry into cyberspace; the average café
charges $US 0.73 per hour, compared to the national minimum salary of
$US 7.00 per month. However, strict licensing requirements have reduced
the number of Tajik cybercafés. In Turkmenistan, private Internet cafés
are illegal, although the government monopoly TurkmenTelecom
operates 15 cafés in the country (OpenNet Initiative, 2010b). Prices in
these cafés in 2007 averaged $US 4/hour (compared to an average
income of $US 100/month), although after President Berdymukhamedov
reprimanded the Minister of Communications for such high charges
they dropped to $US 2/hour. (In 2008 TurkmenTelecom began to offer
dial-up home access, but at such high prices that it is unaffordable to
most residents). Some assert that high fees are an implicit form of
censorship designed to limit Internet access (Lambroschini, 2011). Clark
and Gomez (2011, p. 8), however, argue that rather than fees, it is the
technical skills of staff that make cybercafés accessible to unskilled users:
“In Kazakhstan, while most staff in cybercafés are information
technology students and trained in ICT, most public library and
telecentre staff have almost no ICT training.”
Throughout Central Asia, Internet cafés tend to be clustered in
commercial districts frequented by tourists, particularly business districts,
hotels, and airports. Cybercafés are also major points of government
control over the Internet: those in which customers attempt to access
banned websites are routinely closed, and customers who access
pornography typically face steep fines. However, as Internet penetration
rates climb, including more access at home, the importance of cybercafés
is likely to diminish.
Some governments in the region have also promoted the public
counterpart to private cybercafés. In Kazakhstan there are 460 public Internet
access points, which began in 2006 (Bhuiyan, 2010), and the government has
begun to provide free dial-up access in public schools. The Kyrgyz government
has established 150 public access Internet centers (OpenNet Initiative, 2010a)
and promoted free Internet access through schools, libraries, and even
hospitals and prisons. Even Afghanistan has provided a few public tele-kiosks.
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As in most of the world, the most active Central Asian netizens tend to
be young and well educated, including students, government employees,
and those working for large corporations. In Kyrgyzstan, one-half of users
are students and 75 percent are under age 30. Ninety percent of Uzbek
users have a post-secondary education (Wei and Kolko, 2005). Not
surprisingly, it is often elites situated in urban areas who tend to exhibit
the highest rates of connectivity. In Uzbekistan, for example, 85 percent of
netizens live in urban areas (Wei and Kolko, 2005), 70 percent of whom
are concentrated in Tashkent (Privacy International, 2003; OpenNet
Initiative, 2010c). In Kyrgyzstan, 77 percent of Internet users are located in
Bishkek. In Turkmenistan, 95 percent of users are in the capital, Ashgabat
(OpenNet Initiative, 2010b). The minuscule population of Afghani
netizens is concentrated in Kabul, Jalalabad, and Khost.
Because Internet penetration rates are low, and users tend to be well
educated, often employed by foreign firms, or in touch with Central Asian
diasporas elsewhere, the domestic share of Internet traffic in the region
tends to be low. In Uzbekistan, for example, 90 percent of the country’s
Internet flows are international in scope (ESCAP, 2009, p. 7), indicating
that the web’s use to create or solidify ties among Uzbeks is limited.
In addition to economic, technical, and political obstacles, Central Asian
Internet users often face cultural impediments. The widespread deployment
of English on the web narrows the participation of those unfamiliar with the
language, and English language websites are uncommonly used in Central
Asia. As another testimony to the legacy of the Soviet era, Russian often
remains the most popular language on the Central Asian Internet, although
Russians are a minority people there. Numerous Russian language websites
and search engines exist, sometimes comprising the vast majority, which
gives a significant advantage to the Russian minority and limits Internet
access to non-Russian speakers. Freedom House (2011), for example, found
that 94 percent of Kazakh websites were in Russian. Because local language
websites are underdeveloped, many users see the Internet as a means of
accessing foreign material but as being of limited use in obtaining
information about local events. In some countries, i.e., Afghanistan, low
literacy rates and restrictive gender roles play a role; Afghani women have
the lowest female literacy rates (9 percent) in the world. Even in countries
with high literacy, a significant gender gap remains: in Uzbekistan, for
example, two-thirds of netizens are male (Wei and Kolko, 2005), and in
Tajikistan, more than 77 percent are men.
Censorship and the Central Asian digital divide
Repressive governments often fear the emancipatory potential of
cyberspace, which allows individuals to circumvent tightly state-controlled
media. Central Asia – whose governments have long been known for
authoritarian rule, corruption, political systems that center upon
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The Central Asian digital divide 279
patronage, censorship, and human rights abuses – not surprisingly exhibits
numerous attempts to restrict access to the Internet as well as govern its
contents. A wide variety of methods are used to restrict and/or regulate
Internet access, including applying laws and licenses, content filtering,
tapping and surveillance, discriminatory pricing and taxation policies,
harassment of bloggers (e.g., via libel laws or invoking national security),
hardware and software manipulation, and pervasive self-censorship.
Reporters Without Borders (RWB), an NGO that is the world’s leading
judge of censorship, ranks the world’s governments in terms of the severity
of their Internet censorship. Central Asian countries did not fare well by this
standard (Table 17.5), with the lowest scores (least censorship) found in
Mongolia (23.3) and Tajikistan (32), while Uzbekistan (67.7) and
Turkmenistan (107) – one of the most closed countries in the world – ranked
as two of RWB’s “Internet enemies.” Similarly, the OpenNet Initiative
regularly conducts tests of filtering of websites in Central Asia and finds
frequent, but uneven and often irregular, attempts to hinder access.
McGlinchey and Johnson (2007) studied the divergent censorship paths
found in the region and concluded that in Central Asian countries where
international aid groups and NGOs provide assistance with the Internet
(e.g., infrastructure funding), governments tend to be more permissive
and less restrictive about Internet access. They argue (p. 275) that:
where international NGOs and bilateral and multilateral donors
provide capital and assistance in drafting legislation, such as in
Kyrgyzstan, Tajikistan, and to a lesser extent Uzbekistan, the formal
regulatory framework is more open, clearly articulated, and permissive
of electronic media. ….ICT development demands ongoing negotiations
with and aid from willing foreign partners. And it is the iterative nature
of this relationship that provides Western donors the ability to ensure
conditionality—that is substantive reform—in return for ICT aid.
Table 17.5 Reporters Without Borders scores for Central Asian countries, 2009
Afghanistan
54.2
Kazakhstan
49.7
Kyrgyzstan
40.0
Mongolia
23.3
Tajikistan
32.0
Turkmenistan
Uzbekistan
107.0
67.7
Source: Reporters Without Borders, http://www.rsf.org/en-classement1003-2009.html
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280 Barney Warf
The Nazarbaev regime in Kazakhstan, for example, which can use its oil
and gas revenues to purchase ICT equipment, has received less assistance
from foreign organizations and has thus been relatively free to curtail
Internet access. Nonetheless, since 2009 Kazakhstan has enacted
draconian censorship laws for the Internet and traditional media alike
(Lambroschini, 2011) under the Kazakh Agency for Information
Technology and Communications. ISPs in the country must retain
electronic records of the Internet activities of clients. A Kazakh journalist
from the news website kub.kz, Kazis Toguzbayev, was given a two-year
prison sentence in 2008 for posting an article accusing the regime of
protecting the killers of opposition leader Altynbek Sarsenbayev.
Central Asian Internet censorship takes a variety of forms, and is
typically justified through the excuses of protecting public morality from
decadent or anti-Islamic ideas or combating terrorism and Islamist
extremism. In Afghanistan, Internet usage only began in 2001 following
the ouster of the Taliban, which held that the web allowed foreign and
anti-Islamic obscenities to enter the country. During the 2005
parliamentary elections, the government of Kyrgyzstan launched “ just-intime” denial of service cyber-attacks against opposition party websites, and
the government closed Internet connections to neighboring countries
(Schwartz, 2005). The Kyrgyz government’s botnet used to launch the
attacks also affected servers in the US, whose protests then forced the
attacks to cease. Despite its severe control over non-digital media, Kyrgyz
cyberspace is relatively deregulated and the government has relatively
straightforward rules governing Internet access, which may reflect its
reliance on foreign aid organizations (McGlinchey and Johnson, 2007;
Srinivasan and Fish, 2009).
Uzbekistan and Turkmenistan, two of RWB’s Internet enemies, engage
in widespread and systematic Internet censorship. Uzbekistan’s
government was relatively lenient regarding the Internet until 2004, when
it imposed numerous controls in response to Islamist uprisings. In
Uzbekistan ISPs must operate under government control, the government’s
web filter, Uzpak, enjoys a monopoly over international connections,
monitors all Internet traffic in the country, and the state often shuts down
uzbekistanerk.org and birlik.net, the websites belonging to the largest
opposition parties (Privacy International, 2003; OpenNet Initiative,
2010c). Invoking an older Soviet tradition, Uzbek Internet journalists who
publish criticisms of the government are occasionally forced into
psychiatric hospitals. However, the regime appears to have gradually
liberalized its restrictions on the use of ICT in the hopes of obtaining
more foreign aid. The dictator of Turkmenistan, Saparmurat Niyazov,
strove to keep that country hermetically sealed from the outside world,
essentially converting the country’s Internet into an intranet, although his
successor, Gurbanguly Berdymukhamedov, vowed to open it up to the
global Internet. This promise was belied, however, by the presence of
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The Central Asian digital divide 281
government soldiers at the doors of Internet cafés (Eurasianet.org, 2007)
and government surveillance of all ISPs using deep packet inspection
techniques. As RWB (n.d.) notes, “Opposition websites such as XpoHo.tm
and Gundogar, and regional news sites covering Central Asia such as
ferghana.ru and eurasianet, are blocked.”
A growing community of Central Asian cyber-activists resists these
attempts (see EurasiaNet.org). Across Central Asia, netizens have
struggled to protect Internet freedoms, including in Uzbekistan
(Machleder, 2002), where the Uzbek “For a Free Internet!” campaign has
monitored bills in the lower house of parliament, the Mazhlis, which
attempted to extend the government’s censorship. In Kyrgyzstan, the
Internet and other media played an instrumental role in the Tulip
Revolution of 2005 that led to the ousting of President Askar Akayev. The
Tajik government’s attempts to criminalize some forms of cyber-speech as
libel against the state were met with heated opposition led by Nuriddin
Qarshiboev, head of the National Association for Independent Media in
Tajikistan. Moreover, Tajik cyber-journalists petitioned the government to
abolish the requirement that the president be called “worthy” and
“reliable” every time he was mentioned. More recently, those seeking to
avoid government censorship can download software designed to help
them do so, such as the Canadian “censorship circumvention” program
Psiphon.
The blogosphere has also become an important part of the Internet in
Central Asia, giving rise to new forms of participatory journalism and
enlarging the sphere of public debate. Kyrgyz bloggers, for example, often
see themselves as actively creating a new sphere of civil society through
online forums such as Diesel and AkiPress (Srinivasan and Fish, 2009).
The Kazakh government has encouraged government officials to create
their own personal blogs, but has not been above arresting Internet
activists such as Zhanna Baytelova and Irina Mednikova, who protested
Kazakhtelecom’s blocking of the opposition websites LiveJournal and
Respublika (Freedom House, 2011).
Concluding thoughts
Still hampered by the crippling legacy of Soviet rule, Central Asia has
been relatively slow to be enfolded into the world’s telecommunications
networks. Although fiber optic cables and satellite services have become
more common, usage in this part of the world remains relatively low, albeit
uneven among its constituent countries. Some governments have initiated
the necessary steps to rectify this situation, including investments in
national data networks, fiber links to schools, and deregulation of state
telecommunications monopolies, but progress on this front remains
glacial. Broadband technologies, key to using the contemporary Internet
effectively, remain in their infancy, in part due to exorbitant charges. As a
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282 Barney Warf
result, the Central Asian digital divide is changing largely despite the
region’s governments, not because of them. International diplomatic
pressure and foreign NGOs have played a key role in encouraging change.
In total, more than 17 million Central Asians used the Internet in 2011.
Penetration rates varied considerably, from 2.0 percent (Turkmenistan) to
almost 40 percent (Kyrgyzstan). Particularly notable is the explosive
growth in the number of users, however: between 2000 and 2011 the
population of Central Asian netizens jumped by 10,300 percent, or roughly
52 percent per year. Because domestic ownership of personal computers is
very low, many people – often the majority – rely on cybercafés to access
the Internet, although some governments are promoting Internet use in
schools and public tele-kiosks. Users in these countries are usually young,
almost always well educated, overwhelmingly urban, and predominantly
male. While most of Central Asia has achieved universal literacy, low
incomes and restrictive gender roles still play a key role in shaping the
digital divide. The Russian language is disproportionately reflected in the
region’s websites while webpages in local languages are underrepresented,
adding another obstacle to Internet utilization.
Fearful of democracy and of the Internet’s potential to disrupt the power
of established elites, most Central Asian governments have actively sought to
curtail their residents’ ability to log on and to control the contents of the
webpages they can access. While none of the governments have refused to
interfere, Uzbekistan and Turkmenistan have engaged in the most egregious
Internet censorship. Despite these political barriers, in addition to economic
ones, the region’s Internet users have struggled against censorship,
including a small but active blogosphere of cyber-dissidents.
As the Internet gains traction in Central Asia – a process that is
occurring with remarkable speed – it is likely to have a wide variety of
unanticipated consequences, including the creation of new forms of civil
society and new geographies of centrality and peripherality (e.g., virtual
Silk Roads). Fears that cyberspace may lead to a cultural homogenization,
for example, appear to be unfounded: Wei and Kolko (2005) concluded
that far from simply homogenizing cultures, the Internet in Uzbekistan
facilitated the expression of local languages and literature. The
introduction of e-government to the region may lead to greater
transparency and efficiency in the provision of public services. In short,
the digital divide in Central Asia, while undergoing rapid change,
simultaneously reflects the region’s power relations and becomes a vital
part in their transformation.
References
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Institute for Development Economics Research.
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Bhuiyan, S. (2010). E-government in Kazakhstan: Challenges and its role to
development. Public Organization Review 10(1), 31–47.
Caselli, F., and Coleman II, W. (2001). Cross-country technology diffusion: The
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Clark, M. and Gomez, R. (2011). The negligible role of fees as a barrier to public
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Clarke, G. (2004). The effect of enterprise ownership and foreign competition on
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46(2), 341–370.
Comin, D. and Hobijn, B. (2004). Cross-country technology adoption: Making the
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Compaine, B. (ed.). (2001). The digital divide: Facing a crisis or creating a myth?
Cambridge, UK: Cambridge University Press.
Cooper, M. and Compaine, B. (eds). (2001). The digital divide. Cambridge, MA, US:
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Crang, M., Crosbie, T. and Graham, S. (2006). Variable geometries of connection:
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43(13), 2551–2570.
Davison, R., Vogel, D., Harris, R., Gricar, J. and Sorrentino, M. (2003). Electronic
commerce on the new Silk Road: A cornucopia of research opportunities.
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ESCAP. (2009). Economic development through improved regional broadband
networks: Macro-level study of 4 selected broadband markets in Central Asia.
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WP_7_2_909.pdf
Eurasianet.org. (2007). In Turkmenistan, Internet access comes with soldiers.
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Keller, W. (2004). International technology diffusion. Journal of Economic Literature
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Korupp, S. and Szydlik, M. (2005). Causes and trends of the digital divide.
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Lambroschini, A. (2011). No Twitter revolt for Central Asia’s closed regimes.
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18 The double digital divide and
social inequality in Asia
Comparative research on
Internet cafes in Taiwan,
Singapore, Thailand, and the
Philippines1
Tomohisa Hirata
Kyoto University
Introduction: The double digital divide in Asia
According to statistical data, the proportion of households with the
Internet in Asian countries and some other countries in 2008 can be
shown as follows.
The percentages of households with the Internet in some
“technologically advanced countries” in Asia are higher than or equal to
those in technologically advanced countries in other areas. For example,
the percentage in the United States in 2008 was 62.5 percent and the
average percentage in the five Nordic countries was 82.9 percent. At the
same time, household Internet usage in most “technologically developing
countries” in Asia is equivalent to that in the rest of the world. In fact,
these percentages are similar to those in African countries.
Previous studies on the above situation focused on either the digital
divide in each Asian country (Tarohmaru, 2004; Kagami et al., 2004;
Kumar, 2006) or that across the whole of Asia (Choi, 2000; Quibria et al.,
2002; Evers and Gerke, 2004). Some of them found relationships between
the digital divide and social stratification. On the other hand, others
revealed no relationship between them. However, there have been no
studies that bridge these approaches and their contradictory conclusions.
The purpose of this chapter is to accomplish this task. The term “double
digital divide in Asia” in the title of this chapter indicates both the digital
divide within each Asian country and that across the whole of Asia.2
Methodology: Understanding Asia through the
Internet cafe
To fulfill this purpose, I will consider Internet cafes (ICs) in the
metropolitan areas of Taiwan, Singapore, Thailand, and the Philippines.
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286 Tomohisa Hirata
South Korea
Ave. of 5 Nordic
Japan
Singapore
Taiwan
Hong Kong, China
Brunel Darussalam
United States
Macao, China
Malaysia
China
Philippines
Maldives
Thailand
Viet Nam
India
Ave. of African Countries
Sri Lanka
Cambodia
Mongolia
Bhutan
Myanmar
Laos
Bangladesh
Indonesia
Pakistan
Nepal
0
10
20
30
40
50
60
70
80
90
Figure 18.1 The Proportions of Households with the Internet
Note: The median of the proportion of households with the internet in African Countries
is 1.5%.
Source: This figure was created by the author from data provided by ITU (2010), Taiwan
Network Information Center (2008), and the National Statistical Bureau (2011).
The IC can be defined as a store which offers personal computers (PCs)
and Internet access at a relatively low cost to anyone. I will treat the IC as a
place where technological “have-nots” who want to use PCs and the
Internet can easily become technological “haves,” although only
temporarily. According to my research on ICs in the above countries, they
are used by not only young people, but also international/domestic
migrants3 who are a quintessential example of technological have-nots and
are living in the global labor market and international/domestic
stratification. Moreover, their uses of ICs are quite limited by their
economic, cultural, racial, and political (legal) situations.
By focusing on ICs and their users, I will unravel the relationship
between social stratification and the double digital divide in Asia. In my
consideration, I will briefly refer to Weberian socio-economic theory of
social stratification and some statistical data in each area. However, for the
sake of precise description of ICs and their users, I will use an ethnographic
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The double digital divide and social inequality in Asia 287
approach in most of this chapter like that of Whyte (1993) and Willis
(1981). More concretely, I used three empirical approaches in this
research, as follows:4
1) Mapping ICs: By confirming the disparities in the distribution of ICs
in each area, we grasp not only the financial situations and social
backgrounds of the technological have-nots but also the social
functions of the ICs.
2) A field survey on the efficiency of the PCs, pre-installed software,
usage fees, and additional services in the ICs: PCs can vary in efficiency
and additional devices which are available in accordance with user’s
needs. We can presume that the level of PCs in ICs is minimized to
reduce the cost of installation and maintenance, while at the same
time they are customized to meet most of the main users’ needs. We
see all the possible uses of the PCs for technological have-nots in their
local ICs from this survey.
3) Semi-structured interview research with the shop managers/assistants
of the ICs and their customers: Through this research, we confirm the
basic attributes of the technological have-nots who are found in
surveys 1) and 2) above along with a simple understanding of their life
course. We also clarify the functions of ICs and the basic attributes of
their managers/assistants through concrete examples.5
Thailand: The great barrier of two languages
In 2008, there were at least 500 ICs in Bangkok (National Statistical Office
Thailand, 2008), and its total area is approximately 1565 km2. Almost all
ICs use glass panes for their frontage because their front side must be kept
transparent by law, for ease of patrolling by police officers who check
whether students are skipping their classes to play online games.
In Bangkok, online gaming is a popular use of ICs and this usage relates
to one aspect of the distribution of ICs. In suburban places such as On Nut
and Wongwian Yai, ICs are spreading. In 2011 they were offering high-end
PCs for contemporary online games. Usage fees in this kind of area are
from 10 to 20 THB (1 THB = 0.03 USD6) per hour and most ICs offer some
discount packages for customers staying longer. This tendency can be seen
in the vicinity of some universities where there are many young people.
However, the most concentrated area of ICs is in the Khaosan area (one
of the most famous backpacker zones in the world) and the second most
concentrated area is around BTS Nana station (one of the most famous
nightlife spots in Bangkok).
There were 38 ICs in approximately 0.5 km2 of the central area of
Khaosan and the 1.5 km2 centered on BTS Nana station has 26 ICs. These
ICs sometimes double as travel agencies or hostels for foreign travelers and
their PCs are low-end, only for viewing webpages, e-mail or social
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288 Tomohisa Hirata
networking services. Their fees are almost exclusively 1 THB per minute,
or 10 or 15 THB as the minimum charge.
Let us focus on the common factors of ICs in Bangkok. Almost all their
PCs have Microsoft Windows XP English version installed. This fact
requires shop managers/assistants to have reasonable English skills to
manage the shops. They need to install and modify PCs which have nonnative language operating systems and understand the uses of software on
offer to customers. According to my research, a fair percentage of shop
assistants are university students or have university degrees.
Now, I would like to turn to customers who do not belong to the
categories of gaming users and travelers. A, a junior high school student,
comes to ICs to do her homework two or three times per week. Ms. B, the
mother of A, is from Northern Thailand. After getting married, she had
three children including A; however she is now divorced from her
husband. Now she manages a Thai noodle stand to cover living expenses.
Her income per month is 6,000 THB. Their house rent costs 3,000 THB
per month, so it is very difficult for them to buy a second hand laptop
because this costs at least 6,000 THB or more in Bangkok.7
In contrast, ICs in travelers’ areas have another type of customer. They
are called “bar girls” in Thailand. Some ICs around BTS Nana station
offer extra services for them. One is to resize and upload pictures to
websites. And another is to translate e-mails or letters written in the Thai
language to English. In a shop, it costs 30 THB per mail or 50 to 70 THB
per A4-size letter. The person who translates and uploads them is a shop
assistant.
Ms. C, a shop assistant, told me that those letters are mainly “love
letters.”8 She works at the IC from 7:00 pm to 4:00 am, from Monday to
Friday. She said the characteristics of the customers change at 2:00 am,
which is when all the bars close.
Previous studies on bar girls in Thailand have pointed out that they
were usually born into very poor families in rural areas and they have
often had no chance to gain higher education.9 Ms. C also told me that
almost all bar girls have only graduated from primary school and they
have sufficient knowledge of neither English nor PCs.
Moreover, they can hardly go to relatively cheaper ICs in residential
areas. Regarding this, one of the reasons which Ms. C explained to me is
the bar girls’ pride. That is, some of them feel ashamed to be able to use
neither English nor PCs. We can easily suppose that it would be more
difficult for them to ask shop assistants to help them in residential areas
because this implicitly reveals what kind of job they do. At midnight in the
Nana area, it is not out of the ordinary for customers to be unable to either
use English or PCs.
In the context of the language problem, another barrier to accessing
ICs should be mentioned. There are from 1.5 to 2 million10 migrants from
Myanmar in Thailand and most of them are engaged in dirty, difficult,
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The double digital divide and social inequality in Asia 289
and dangerous low-paid work (Amnesty International, 2005). However I
could not find them in ICs in Bangkok and the shop managers/assistants
never referred to them as customers of their shops.
From the above discussion it is clear that ICs in Bangkok sometimes play
a role in solving social stratification which derives from economic,
cultural, and racial factors but sometimes do not. As one significant factor,
the language skill required to access PCs and the Internet – English and
Thai language – was focused on.
The Philippines: Ubiquitous skills, class and status
Incidentally, the specificity of language as a skill is that it is not only a skill
but also that the value of language as a skill is transformed in different
cultural contexts. The situation of Metro Manila is an example where this
can be seen. As a reference to comprehend the total number of ICs in
Metro Manila, let us see the number of ICs which had business permits in
2010 in the cities of Manila, Pasay, and Quezon.
Fourteen hundred twenty-nine shops are located in 218.67 km2, which is
approximately one-third of the total area of Metro Manila (639 km2). This
means ICs are extremely numerous in comparison with Bangkok. All the
PCs in ICs in Metro Manila have Windows XP English version installed.
The usage fees are from 15 to 30 PHP (1 PHP = 0.02 USD) per hour and
some shops offer discount packages.
Table 18.1 ICs in three municipalities in Metro Manila
Municipality
(Area)
Manila
(38.55 km2)
Classification of
ICs by Nature of
Business
Internet Cafe
198
Computers for
Education
203
Computer
Games
490
Internet Cafe
Pasay
(19.00 km2)
Quezon
(161.12 km2)
Total
(218.67 km2)
The Digital Divide_BOOK.indb 289
Sub Total
Number of ICs
Total Number
of ICs
Average Density
of ICs
(Shops/km2)
891
23.11
200
10.52
92
Computer
Rental (and
Internet)
108
Internet Cafe
338
338
2.09
—
1429
6.53
—
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290 Tomohisa Hirata
According to a summary of the 2000 Census of Population and Housing,
81.57 percent of the total household population aged five years old and
over can speak English in Metro Manila (National Statistics Office, 2005).
So they can use PCs in ICs easily. However, this implies that having English
skills is not an advantage over others, but rather a required skill not to
drop to a lower segment of society.
In fact, the wages of shop assistants in ICs in Metro Manila are almost
the legal minimum wage (426 PHP per day) or lower. In contrast, the
average income of IC shop assistants who I interviewed in Bangkok was
8,000 THB per month. This is considerably higher than the minimum
wage (215 THB per day) per month in 2011 (Bank of Thailand, 2011, p. 2).
Let us consider the concentrated areas of ICs in Metro Manila. The
most concentrated area of ICs is in 2.25 km2 centered near the University
of the East in the City of Manila. This area has 92 ICs, 5 universities and 3
colleges. So, ICs in this area can attract young customers. These areas have
two types of ICs. According to Table 18.1, they are divided into “Computers
for Education” and “Computer Games.” The former mainly offer PCs with
relatively low efficiency to students who need to write reports or collect
data to get better grades but do not have their own PCs. The latter provide
high efficiency PCs for anyone wanting to play online games.
The second most concentrated area is in Pasay City. There are 35 ICs in
approximately 1.0 km2 around LRT Libertad station. In an IC around this
station, Ms. D, a shop assistant, told me that there are of course gaming
users in this shop, however, some residents in this area do not have their
own PCs, and some do not have enough money to pay for Internet access.
This situation is not a rare case in Metro Manila, and these people use
ICs for two main purposes. The first one is job hunting. In the abovementioned IC, some adults write their CVs using PCs sometimes bringing
their children, and some use the Internet for job-seeking.
In Weberian theory, classes are defined as “groups of people situated
similarly in relation to commodity or labor markets on account of their
possession of capital or skills” (Witte and Mannon, 2010, p. 87). According
to Weber, “Ownership or non-ownership of material goods or of definite
skills constitutes the ‘class-situation’” (Weber, 1946, p. 405).
At first this situation fits with that in ICs in Bangkok. However, as we saw,
most Filipinos in Metro Manila have English skills to access the Internet and
PCs easily. Additionally, ICs accelerate this tendency because they play a role
in diminishing the problem of capital possession. As a result, the possession
of English skills itself is relatively devalued and this increases the competition
in job hunting in Metro Manila compared to some other Asian countries.14
Another use of ICs in residential areas is contacting relatives and friends
who work in foreign countries using English skills. The total number of
overseas Filipinos as of December 2009 is 8,579,378 (Commission on
Filipinos Overseas, 2009) and this number is 9.29 percent of the total
population (National Statistics Office, 2012) in the Philippines.
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The double digital divide and social inequality in Asia 291
Table 18.2 The number of overseas Filipinos by country and their status
Country
Singapore
Taiwan
Total
Permanent (%)
Temporary (%)
Irregular (%)
47,770 (26.22) 64,320 (39.44) 56,000 (36.34)
8,328 (8.83) 83,070 (88.11)
Total
163,090
2,885 (3.06)
94,283
51,098 (19.85) 147,390 (57.27) 58,885 (22.88)
257,373
Source: This figure was created by the author from data provided by the Commission on
Filipinos Overseas (2009).
The number of overseas Filipinos and their situation in Singapore and
Taiwan are as above. Table 18.2 clearly shows that most Filipinos in both
countries are temporary and irregular. But why do they go? The reason
why they travel abroad for work is not only to get money in relatively stable
positions but also for a chance to improve their and their families’ social
status in Weberian terms. According to Weber (1946, p. 405), status is “a
quality of social honor or lack of it, and is in the main conditioned as well
as expressed through a specific style of life.”
In my survey, overseas Filipino workers (OFWs) used the term “sacrifice
for my family” to describe their situation. Actually almost all of them work
abroad in order to earn money to cover their children’s school expenses,
which are sometimes for tuition fees for private schools. These schools
offer a better learning environment but their fees are very expensive for
ordinary people.
Status takes shape in stratification which is “rested on honor, or
prestige, rather than on economic assets” and in addition, “family
background and occupational group” play “an especially important role in
distinguishing one’s status position and hence, one’s lifestyle choices”
(Witte and Mannon, 2010, pp. 87–9) in Weberian theory. In this sense, ICs
play a role in demonstrating that their status is improving to OFWs and
their families. That is, in the precise moment when they and their families
use the ICs for communication, ICs provide them with the evidence that
the quality of their lifestyle is gradually getting higher. In the following
section, we will see some examples of status stratification in the manner of
use of ICs in Singapore and Taiwan.
Singapore and Taiwan: Status stratification in migration
and childcare
As we saw in the first section, Singapore and Taiwan belong to the group
of technologically advanced countries. So, all the shop assistants
interviewed in ICs in Singapore and Taipei unanimously said that ICs are
decreasing in number. However, ICs do not disappear even in these places.
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292 Tomohisa Hirata
Or rather, there are still many ICs for migrants. The fees are also very
cheap. For example, fees in Singapore are mostly from 0.6 to 2 SGD
(1 SGD = 0.78 USD) per hour, and those in Taipei are from 20 to 30 TWD
(1 TWD = 0.03 USD) per hour.
For now, let us confirm the places where OFWs come together in these
cities.11 Lucky Plaza is a big shopping mall in Singapore where there are
many OFWs. It has eight ICs and other shops aimed at OFWs such as
money transfer shops and employment agencies. On their holidays, the
OFWs use PCs for communicating with their relatives and friends.
Ms. E is from the Northern part of the Philippines. She has worked as a
domestic helper in Singapore from 2009. After learning how to use PCs
with the help of her employer, she often comes to ICs to communicate with
her relatives. However, now she wants to buy her own laptop because in ICs
there are sometimes people who complain loudly about the Internet and
PCs and it is disturbing.
Regarding this, Ms. F, an OFW and a shop assistant in an IC in that
mall, told me that nuisances in her work are complaints from those kinds
of customers. However, she also told me with a smile that this job is not too
stressful because she does not need to be polite to customers, most of
whom are OFWs.
Similarly, there are four ICs in a small building in Taipei City, near
which many OFWs come together. Mr. G, an OFW and a shop assistant in
an IC in this building, told me that the shop is only for OFWs and therefore
it makes money only in their holidays. In fact, its PCs have Windows XP
English version installed and an advertisement saying “We Assist Visa to
Canada” is shown on the wall. He also said that no customers annoy him
because they are all Filipinos.
The above situations can be understood through the relation between
class and status in Weberian theory. Weber (1946, p. 405) said that status
membership “influences the class-situation in that the style of life required
by status groups makes them prefer special kinds of property or gainful
pursuits and reject others.” Ms. E and Ms. F’s thoughts about nuisances are
based on their image of the ideal skilled IC user whom every IC user should
aim to become. They also apply this ideal to OFWs’ use of the IC. However,
Ms. F and Mr. G both felt relaxed in their ICs. It is clear that this feeling is
derived from the fact that these ICs become places in which mainly OFWs,
who belong to the same class when in foreign countries, come together.
In contrast, a few ICs for gaming use are in middle-sized shopping malls
in residential areas in Singapore. According to regulations stated by the
Singapore government, ICs for gaming use are not allowed “to be set up in
HDB residential zones” (Ministry of Home Affairs, 2007). The Housing
and Development Board offers public housing (HDB flats) for
Singaporean citizens and permanent residents at low cost. I found a few
ICs on the first floors of HDB flats for migrants, however one of them had
the warning “Online Gaming is strictly not allowed” on the wall.
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The double digital divide and social inequality in Asia 293
In Chinatown in Singapore, some young children were playing games
in an IC in the late evening. Mr. K, the manager of this shop, told me that
almost all their parents are divorced and live in old and cheap HDB flats
nearby. These single-parents who need to work a lot at night have neither
enough time to care for their children nor enough money to employ
housemaids. They do not buy PCs because they think there is no need.
All they can do for their children is to give them 10 SGD per day as an
allowance. As a result, the children have no choice but to go to ICs
because they are all alone in their home and no shops except ICs are
open until evening. The regulations only require ICs “not to admit
persons below 16 years of age before 6.30 pm on a school day” (Ministry
of Home Affairs, 2007).
In Taipei City, the most concentrated area of ICs is around Taipei
Railway station and Ximen station, there are 13 ICs in 0.66 km2. However,
many ICs are in New Taipei City, a suburb of Taipei City. In fact, half of the
total number of ICs which had business permits in 2011 (256 shops) in
New Taipei City are in five districts near to Taipei City, although the total
area of the five districts is only 6.05 percent of the New Taipei City area.
These ICs are mostly for gaming use.12
In this situation, recently some parents have been using ICs as substitutes
for An-qin-bans (Liu and Huang, 2011),13 a kind of childcare facility for
elementary school children. They have also played the role of private
tutoring schools and have supported Taiwanese women who work after
childbirth. However, their costs are very expensive, from at least 4,000 TWD
to, at maximum, 10,000 TWD per month (Fukaya, 2008, p. 196).
So, if parents do not have enough money to pay for An-qin-bans, but they
want to give their children a relatively safe space where someone watches
over them, it is possible that they let their children go to ICs as a substitute
for An-qin-bans. However, from a legal viewpoint, parents cannot use ICs for
this purpose in Taiwan. Taking an ordinance enacted in Taipei City as an
example, IC managers/assistants “shall not admit people less than fifteen
years of age, unless accompanied by parent(s) or guardian(s), into business
sites” (Law Regulation Database in Taipei City, 2002).
These two cases show us that some children whose families belong to
lower economic groups in Singapore and Taipei City sometimes have no
choice but to use PCs and the Internet in ICs. Their parents are trying to
keep their status in their own way for example by providing a safe space or
a minimum allowance for their children. They seek what is called “good”
but this is sometimes incompatible with another “good.”
So, we can treat these families as a case of class and status stratification
in Weberian theory. Because, especially for the children, their family
background imposes IC use on them as a lifestyle as in class. From this
viewpoint, we can see Ms. D’s situation as a similar case because now she
uses PCs only for communicating with her relatives although she has the
PC skills to use it for other purposes. Investigating these ICs plays a role in
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294 Tomohisa Hirata
distinguishing those people who can use PCs and the Internet without ICs,
from others who have no choice but to use ICs to access these lifestyles.
Conclusions: Rethinking the digital divide in Asia
From the above discussion, we revealed that capital for an educational
environment that offers the opportunity to learn something, including the
IT skills and the required language skill, is a crucial factor for the digital
divide in every case. In this sense, it is true to some degree that, as some
previous studies have pointed out, the capital for an educational
environment (including private and public environments) is a key factor in
solving the problem of the digital divide in Asia.
However, it is also true to some degree that other previous studies have
found that the gap of the digital divide in Asia is decreasing (or is expected
to in the near future) especially from the viewpoint of capital such as GDP,
some of which is used for educational purposes. In fact, ICs in Bangkok
and Metro Manila play an important role in diminishing this gap, and it is
highly likely that the global labor market accelerates this tendency. As a
result, there is a possibility for the migrants and children we saw in the
above section to be ignored in these two approaches because they can be
treated as having the skills to access PCs and the Internet, and their
situation can be regarded as a transition to a “more equal” society.
So our task is to focus on the diversity of choices which is the final goal
of education and IT. More concretely, further subjects for research in
terms of the double digital divide in Asia will be: 1) to seek ways of
broadening peoples’ choices for their lives through their current uses of
PCs and the Internet, and 2) to consider ways of realizing a society which is
open to a diversity of peoples’ choices.
References
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Aoyama, K. (2009). Thai migrant sex workers: From modernisation to globalisation. New
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Ghanaians living abroad/ New Media & Society 10(2), 203–224.
Chen, W. and Wellman, B. (2004). The global digital divide – within and between
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Commission on Filipinos Overseas. (2009). Stock estimate of overseas Filipinos as of
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Ehrich, R.S. and Walker, D. (2000). Hello my big big honey! San Francisco, CA, U.S.:
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digital
divide into digital dividend’
International Telecommunication Union, (ITU). (2010). Measuring the information
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Notes
1This work was supported by a JSPS Grant-in-Aid for Research Activity Start-up
(21830052) and The Kyoto Erasmus Program: A Program for the Overseas
Development of Future Research Project Leadership on Sustainable Social
Development in Asia.
2From the same perspective, Chen and Wellman (2004) discuss the global
digital divide in and between the U.S., the U.K., South Korea, Japan, Germany,
Italy, China, and Mexico.
3Regarding international migrants’ uses of ICs in Europe and Middle East, see
also Burrell and Anderson (2008) and Warf and Vincent (2007).
4The following surveys have been conducted two or three times in each area by
the author. The periods were as follows:
Taipei: February 13–16, 2010; September 12–27, 2011.
Singapore: June 1–7, 2010; August 15–19, 2010; August 8–16, 2011.
Bangkok: February 23–March 1, 2010; July 23–August 8, 2011.
Metro Manila: March 1–10, 2010; August 16–31, 2011.
5The number of informants in each city is approximately 20. When conducting
daytime interview surveys in each city, I did so with the aid of interpreters.
6All exchange rates in this chapter are as of May 30, 2011.
7Regarding the problem of access to computers for children, political moves and
plans for solving it repeatedly came to naught because of their insufficient
investigation into the socio-economic situation in rural areas in Thailand
(Hongladarom and Entz, 2003, pp. 13–6).
8A similar phenomenon occurred in the previous medium, handwritten letters
(Ehrich and Walker, 2000, p. 7).
9For example, see Aoyama (2009).
10This number includes temporary and illegal migrants.
11Especially in Singapore, there are some other concentrated areas of ICs where
migrants come together such as Little India (Indian migrants) or Geylang
(Chinese migrants).
12Additionally, some commuters who work at night in Taipei City use ICs for
taking a rest.
13The case to which I refer here is in Takao City, but there are similar cases in
Taipei.
14Regarding this, many informants evaluated the IC as both a good and bad
place for children from the viewpoint of ease of access to information. In fact,
all ordinances relating to ICs enacted by the above three cities referred to
protection from pornography as their purpose.)
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19 Dimensions of the mobile
divide in Niger
Gado Alzouma
American University of Nigeria
Introduction
The rapid appropriation of information and communication technologies
in Africa has sparked an abundant literature centered on the
“transformative” character of computers and mobile phone technologies.
For many authors (Davison et al., 2000; Steinmueller, 2001; Fleming, 2003;
Waverman et al., 2005) ICTs use will enable Africa to achieve leapfrogging
development. That is why a number of international organizations and
agencies have now placed ICTs at the heart of their development strategies
through programs and projects centered on education, health, trade,
governance, gender, etc. In recent decades these initiatives have been
particularly concerned with the way computers and the Internet can be
used to promote and foster both the economic and the social well-being of
African communities. However, with the advent of the mobile phone, it is
around the possible leveling effect of this technology, that much
developmentalist discourse tends now to focus (Hyde-Clarke and van
Tonder, 2011). It is argued that the mobile phone, unlike the computer, is
ubiquitous, cheap, offers innovative functions (such as the ability to access
the Internet), and presents few barriers to adoption by all social strata and
classes, including the poorest. More and more scholars and development
actors now believe that it will be the use of the mobile phone that will
finally reduce, if not eliminate, the digital divide. Authors like Geser note,
for example, that “by being adopted, irrespective of education and family
background, the cell phone bridges at least some gaps between different
social classes” (Geser, 2004, p. 6). For his part Boyera writes: “One of the
most promising directions to bridge the Digital Divide is to provide
eServices on mobile phones” (2007, p. 1). In those arguments, the
underlying assumption is that having or not having the technical object is
the main barrier or inequality between users.
In contrast to these statements, this article takes a more cautious
approach and argues that the digital divide, as recently emphasized by
Witte and Mannon (2010), has many dimensions and should not just be
viewed as the sole difference or inequality in terms of physical availability
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or access to ICTs, particularly the mobile phone. The mere possession of a
technical object, including access related to the Internet using that
technology, e.g., a mobile phone, does not eliminate inequalities between
those who possess it. Multiple levels of access do exist that are closely
linked to the position that agents occupy in the social space and that will
vary, depending on the degree of economic, social, and cultural resources
these agents are endowed with. Using a Bourdieusian framework, this
paper identifies some of these inequalities as they exist in Niger. It also
explains how differences and inequalities are manifested in both intensity
of use and opportunities for use. The paper is partially based on statistics
from some international organizations – the International Monetary Fund
(IMF), the International Telecommunication Union (ITU), and the
United Nations Procurement Division (UNPD) – concerning access to
ICTs in Niger. These sources are complemented by a few groups of data
collected using semi-structured interviews during the summer of 2011
from rural Nigerien mobile phone users who seasonally migrate to
Niamey, the capital city of Niger.
The paper has three main parts. The first presents the sociology of
Bourdieu in its relation to the sociology of Weber, in its relation to the
concepts of inequality and social class, and the way the “WeberoBourdieusian” theoretical heritage can be used to explore and explain the
digital divide. The paper then presents Niger in the context of the global
digital divide with a particular focus on its (the digital divide’s) economic
dimensions and how the inequalities in terms of access to ICTs and the
Internet are manifested at the Nigerien national level. The last part
examines the cultural, symbolic, and social dimensions of the digital
divide and emphasizes certain aspects that are often not addressed in the
literature.
Theoretical framework: From Weber to Bourdieu
The sociology of Bourdieu borrows from Marx, Durkheim, and Weber.
However, the Weberian theoretical heritage in Bourdieu’s work is more
explicit in certain of his texts than in others (Bourdieu, 1971). The
Weberian legacy is most evident in Bourdieu on issues of inequality,
social class, domination, and the concepts of field and habitus. Bourdieu
particularly took up, from Weber, the idea that inequality has an
economic dimension (resulting in the existence of social classes), a social
dimension (status, in the hierarchical sense of that word, depends on the
positions occupied by agents), and a political dimension. These three
dimensions are three orders of phenomena or three hierarchies that do
not always overlap. For Bourdieu, one can understand them as forms of
unevenly distributed resources for the possession of which the members
of a society (structured as various fields) are engaged in a permanent
struggle. The resources that are available to individuals and groups, the
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Dimensions of the mobile divide in Niger 299
resources they can mobilize, constitute their capital, an economic
concept borrowed from Marx that Bourdieu extended to cultural,
symbolic, and social aspects, following, in so doing, Weber. The capital
presents itself in three forms:
as economic capital, which is immediately and directly convertible into
money and may be institutionalized in the forms of property rights; as
cultural capital, which is convertible, on certain conditions, into
economic capital and may be institutionalized in the forms of
educational qualifications; and as social capital, made up of social
obligations (“connections”), which are convertible, in certain
conditions, into economic capital and may be institutionalized in the
form of a title of nobility (Bourdieu, 1986, p. 242).
The capital, in all its forms, can be accumulated and transmitted from one
generation to another just as it can be won or lost over time. This capital
inheritance explains the constant reproduction of inequalities over time,
and their expansion and reconfiguration, which when combined, give its
structure to the society. Thus, Bourdieu states that:
the structure of the distribution of the different types and subtypes of
capital at a given moment in time represents the immanent structure
of the social world, i.e., the set of constraints, inscribed in the very
reality of that world, which governs its functioning in a durable way,
determining the chances of success in practices (1986, p. 241).
What Bourdieu means is that, in all spheres of social activity, agents act
under structural constraints and within the limits of the capital they are
endowed with, based on the possibilities offered by the position they
occupy.
From this perspective, analyzing the digital divide would be tantamount
to examining how the differential distribution of capital (under its various
forms) is manifested in and governs the access to the Internet in Niger.
Therefore, the differences, or more precisely the inequalities which will be
discussed in the following text, are not only those existing between the
users who have access to the Internet and those who do not have access
(“haves” and “have-nots”), namely, those inequalities that exist between
countries and between individuals and groups based on the level of their
wealth or their income. These inequalities are important, and it is they
that will be presented and analyzed in the first instance. However, this
paper also focused on differences in position or the inequalities that exist
between those users that do have access to the Internet or the mobile
phone. Unlike the first (the economic forms of inequality), the latter are
understood as being the result of an uneven distribution of both the
cultural and the social capital.
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Access to the Internet in Niger
With the notable exception of the mobile phone penetration rate of 24.5
mobile phone subscriptions for 100 inhabitants, ICT indicators are very
low in Niger. The International Telecommunication Union’s 2011 report
on ICT development ranks Niger among the two last countries in the world
with an ICT Development Index (IDI) of 0.92 in 2010 (ITU, 2011, p.13).
That same year (2010), only 1.2 percent of Nigerien households had a
computer and only 0.2 percent had access to the Internet.
Because of their high cost, computer ownership, Internet subscriptions
as well as traditional forms of access to the Internet (including cybercafés)
are out of reach for the vast majority of the Niger population. Indeed,
access to the Internet is far more expensive in Niger than it is in most
developed countries: “Experts say that this cost is 500 times fold the actual
rate in Europe” (Ibrahim, 2007, p. 121). However, it has also been
suggested that the effect of the difference on access between countries like
Niger and developed countries is mitigated by the multiple means or
“locations” of use such as defined and listed by the ITU: “home, work
place, place of education, another person’s home, community Internet
access facility, commercial Internet access facility, any place via a mobile
cellular telephone, [and] any place via other mobile access devices” (ITU,
2010, p. 19). Users who use other means or locations are much more
numerous than those who access the Internet through a computer they
own or those who subscribe to the Internet “by a factor of 2–3 in developed
countries and more in developing countries” (World Bank, 2009, p. 159).
That is why certain authors (Kwaku and Lemaire, 2006; Boyera, 2007)
argue that the nature of the global digital divide could be changed with a
wider access to the Internet through mobile phones because access to
mobile phones is far higher than access to computers, particularly in
developing countries.
Therefore, the inequality between Niger and other countries is far less
important when it comes to mobile phone subscriptions (24.53 for 100
inhabitants in 2010) than it is when it comes to Internet access. This
difference in the access to the Internet and the access to mobile phones is
principally explained by the lower cost of mobile phones compared to
computers. Even in a country like Niger, many people who are defined as
“poor” have a mobile phone albeit to a lesser extent than those defined as
having high income. However, only a tiny minority of the population owns
computers, principally because of their cost. Therefore in Niger, like
elsewhere in the world, the economic capital is the determinant factor in
Internet access and use.
However, as will be seen below, the crude figures that help capture the
inequalities in economic capital and thus access to the Internet also hide
other important disparities between users. Some of those disparities are
for example location (rural/urban) or education, which are often
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Dimensions of the mobile divide in Niger 301
correlated with income but also with the types of technical objects used,
the patterns of use. Those disparities are better understood in terms of
other elements of Bourdieu’s theory, namely social capital and cultural
capital.
Dimensions of the digital divide at the national level
The rural-urban divide
In Niger, the first difference between users is the difference that exists
between urban users and rural users. Because most telecommunication
infrastructure, services, and opportunities to access the Internet are
concentrated in the cities, urban residents have a higher opportunity for
access to the Internet than rural residents:
Niger has witnessed a huge telecommunications penetration,
particularly as a result of mobile telephony with subscriptions
increasing from 57,541 in 2002 to 546,094 in 2006... However, despite
this significant increase, 79% of the rural councils (169 councils out of
213) are not covered by fixed telephone or GSM telephony. 84% of the
rural councils (178 councils out of 213) are not covered by GSM (IMF,
2008, p. 61).
The rural-urban disparity is, therefore, very high in Niger.
In addition, in Niger, rurality is correlated with poverty, illiteracy, and the
general deprivation of populations with respect to the possession of
technical objects. For example, if one defines poverty as “a state of individual
or collective destitution which places man in a situation of shortage or lack
of essential needs” (IMF, 2008, p. 17), the need to communicate could be
understood as one of those basic needs. So while general poverty is very high
in Niger (affecting 63 percent of the population according to the IMF), it is
even higher in the rural areas: 65.7 percent in rural areas and 55.5 percent
in urban areas (IMF, 2008, p. 19). It should also be noted that the urban
poor live in peripheral areas of the cities “on under-developed plots or
lands” (IMF, 2008, p. 20), which lack adequate basic infrastructures and
facilities of all sorts, including communication facilities.
Finally, even among those who do have access to ICTs, opportunities to
use them, the degree of use and the intensity of use will vary depending on
whether one is a rural or urban user. The INS-PNUD survey (2009) shows
for example that rural people, unemployed workers, and people with a low
level of education use mobile phone less often than do urban dwellers or
those with a high/higher level of education. This second group of users
also spends much more on their mobile phone than does the other group.
The average expenditure in mobile telephony is higher in urban areas
than in rural areas. However, while rural people spend less on their mobile
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302 Gado Alzouma
phones than do city dwellers, these expenses also account for a larger
share of the rural household budgets than for urban household budgets.
Among rural people and the poor (in both rural and urban environments),
expenditures on mobile phones, although low, weigh more on other
expenditures that are essential, such as clothing and food. Therefore, the
desire to join the technical universe often produces indebtedness among
the members of this group. These differences in expenditures and the
effect of expenditures on mobile telephony can further reflect class
inequalities that constitute, according to Witte and Mannon, the main
dimension of the digital divide: “The most consistent and striking sources
of variation were found along the traditional markers of class, namely
education and income” (2010, p. 113). Education in general, or what
Bourdieu calls cultural capital, is an important dimension of the digital
divide in Niger as well.
Mobile phones and illiteracy
According to Bourdieu, “any given cultural competence (e.g., being able to
read in a world of illiterates) derives a scarcity value from its position in the
distribution of cultural capital and yields profits of distinction for its
owner” (1986, p. 243). In the same way that the economic capital is
unequally distributed between agents and, therefore, yields different
profits and successes (such as differential access to ICTs), literacy, which is
a dimension of the cultural capital is also unevenly allocated and yields
specific forms of profit. Therefore, the cultural capital (such as higher
education), because it can be converted into economic capital, is one
means of “appropriating the accumulated and objectively available
resources” (Bourdieu, 1986, p. 243), among which are technical objects
(cars, televisions, computers, mobile phones, etc.). We should also
understand “appropriation” in the sense of “domestication,” namely the
possibility and opportunity given to different users to master technical
objects and use them for their own benefit. Indeed, ICTs are probably the
best example of the cultural capital in its “objectified state,” in other words
the cultural capital as “objectified in material objects and media,” or the
immaterial (knowledge) made material, tangible. Although the cultural
capital is “transmissible in its materiality” (Bourdieu, 1986, p. 243), the
possibility to own, appropriate or master advanced technical objects, such
as computers (and even, to some extent, own and use mobile phones) still
depends on cultural competencies (technical, literacy or educational skills
for example) of social agents. Nowhere else is this more obvious or
important than in Africa where illiteracy still prevails in large sections of
society.
For example in Niger over 60.1 percent of adults cannot read or write
(at least in languages used in Western-style or modern education; i.e.
French in the case of Niger). These rates are even more important when it
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Dimensions of the mobile divide in Niger 303
comes to gender literacy since 80 percent of women can neither write or
read (Macro International, 2007). Illiteracy is thus the biggest barrier to
Internet access. It (illiteracy) is an obstacle that cannot be surmounted
either by the implementation of cybercafés in rural areas or by free access
to multipurpose community tele-centers. As Parkinson says:
People using computer-related services (in telecentres) tend to have
higher levels of education (secondary or above) and often have had
some prior exposure to computers through school, work, or are
introduced through a friend or family member... telecentres, have not
proven a robust method of overcoming the multiple barriers to access
that many people face (2005, p. XVII).
It could be added that the possession of new generation mobile phones
that certain authors hail as a panacea for Internet access does not remove
the illiteracy barrier. It can be seen in the relatively higher degree of
access to other information and communication technologies among
Nigerien households irrespective of income. For example, neither the
cost of radio, nor the cost of television, let alone the cost of a mobile
phone, has become a barrier to their possession to the same extent that
illiteracy has for overall Internet access. Thus, in 2006, 73.1 percent of
urban households and 56.6 percent of rural households in Niger did own
a radio; 34.1 percent of urban households and 6.2 percent of rural
households had a television, and 6 percent of urban households and 0.7
percent of rural households had a fixed line telephone (Macro
International, 2007). Then, it can be said that the main reason for
possessing radios, televisions, and telephones is that their users do not
need to know how to read and write to use them. However, these same
individuals cannot access the Internet if they are illiterate, no matter
their economic capital; people may well have the material means to
appropriate cultural goods (namely the economic capital) at least
relatively as in the case of radios, televisions, and mobile phones, and yet
lack the symbolic means (the cultural capital) to access technical goods
(computers and the Internet). As Bourdieu says:
To possess the machines, he (the social agent) only needs economic
capital; to appropriate them and use them in accordance with their
specific purpose (defined by the cultural capital, of scientific or
technical type, incorporated in them), he must have access to
embodied cultural capital, either in person or by proxy (1986,
p. 243).
By “appropriate,” Bourdieu means the capacity, for a social agent endowed
with the required skills or technical competencies, to master and use a
technical object in accordance with his/her intended goals. These skills
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304 Gado Alzouma
and competencies are part of his/her habitus, i.e., the dispositions
cultivated in him/her, the know-how (savoir-faire).
They (the skills and competencies) have obvious consequences for
patterns of mobile phone use. In Africa, most users use the mobile phone
only to call and receive calls. While the use of SMS is especially popular
among young educated people (Vold Lexander, 2011), it is not so for all
users. Those who do not know how to read and write do not use SMS or
only rarely use it, often in a limited way. For example, Z, who usually uses
intermediaries to read SMS or save names of callers, says:
I sometimes receive messages but most of the time I receive phone
numbers that I have asked for. I know which buttons to press to see the
number and save it. Although I am illiterate I know how to read numbers
one after the other.
Finally, illiterate people mainly use a mobile phone to maintain contact
with family members and for business. These limited uses of the mobile
phone principally characterize those users who are weakly endowed with
cultural capital (literacy and digital literacy). The lower the cultural
capital, the more limited the number of uses. More importantly, in
countries like Niger and most African countries, social agents lack, to a
certain degree, both economic capital and cultural capital; therefore, the
overwhelming majority use mobile phones under that double constraint.
The mobile divide: Poverty, lifestyle, and phone use
“You have to try, to try, to try...” In terms of cultural capital, it could be
argued that mobile phone ownership and use is part of the lifestyle, which
for Bourdieu manifests a set of tastes, beliefs, and practices that
characterize a specific social class or a fraction of a social class. The
lifestyle is the product of the living conditions which in turn generate a
different class habitus:
Because different conditions of existence produce different habitus...
the practices engendered by the different habitus appear as systematic
configurations or properties expressing the differences objectively
inscribed in conditions of existence in the form of systems of
differential deviations which... function as life-style (Bourdieu, 1984,
p. 190).
The habitus operates under structural constraints (the capital owned by
agents and their position in the field; for example the field of technology
consumption) that restrict both possible choices and direct actions. In this
respect, it is well known that the mobile phone, at least in its beginning,
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Dimensions of the mobile divide in Niger 305
was a sign of distinction (a status symbol for Katz and Sugiyama, 2006) for
some classes and the manifestation of conspicuous consumption in the
same way that the ringtone, the mobile phone color, its brand and its
functionalities express today personal choices that are widely associated
with a certain lifestyle. As a sign of conspicuous consumption, the mobile
phone reflects the possession of a certain degree of economic capital and
as a sign of social distinction denotes the possession of a particular social
and cultural capital.
It is especially evident in societies, such as the Nigerien society, where
class differences espouse extreme configurations, with wide gaps (in
income) between groups of unequal economic status that the weight of the
habitus regarding consumption choices becomes the greatest. This is
particularly salient in terms of the ownership of mobile phones whose
apparent “democratization” and apparent “levelling effect” (Geser, 2004)
conceal in fact deep inequalities.
One of those inequalities (which also marks the ownership of
computers) is the kind of device that users own, its level of performance,
its condition, and the functionalities it offers. As noted earlier, the new
mobile devices (Smartphones) have more advanced features than the
ordinary mobile phones do: One can browse the web, as well as access
social media and send mail (using SMS). Audio and video functionalities
(camera, radio, television and photography) are also available; but these
phones are generally more expensive (in Niger they cost a minimum of
US$ 50 or one-fifth of the annual income of the average citizen) and only a
tiny minority of people can afford them. Indeed, even the cost of the
cheapest mobile phone seems prohibitive in terms of the average
Nigerien’s income: “The price of the cheapest mobile phone... in Niger is
equivalent to 12.5 kilograms of millet, enough to feed a household of five
for five days” (Aker and Mbiti, 2010, p. 5). This is a first level of inequality
since the majority of mobile phone users buy inexpensive and less efficient
devices. In addition, 37.6 percent of users say they acquired their phones as
a gift (INS-PNUD, 2009), which is some indication of the group’s
extremely low purchasing power. The devices they own cannot perform
most of the functions people in developed countries take for granted:
Many of the low-end handsets found in the markets and shops in
developing countries [have] no browser of any kind and [do not]
support GPRS (General Packet Radio Service) or any other form of
data transmission... But this is not the only problem. Network coverage
in many rural areas lacks data support even if the phones did have it,
although this is admittedly changing (Banks, 2008).
Even when the region is covered, rural users are often confronted with a
weak signal or absence of signal altogether, depending on where they are
located in their villages. One of my interviewees told me that they have to
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306 Gado Alzouma
walk outside of their village to be able to make calls or hear calls.
Therefore, calls cannot be received or made on a regular basis or at will.
They are often “planned ahead of time” or made through individuals in
the village who are located near where calls can be received. Calls are also
often missed or “cut” (dropped) during conversations and users have to
resume the process. As another of my interviewees told me: “You have to
try, to try, to try...” thereby underlining the tedious, time-consuming and
frustrating aspect of a phone call in some Nigerien rural areas. Along with
the cost, this situation has consequences in terms of the quality of the
conservations and their length because conversations are most often
shorter or halted (Alzouma, 2006, 2008).
For the same reasons, what people use their phones for (call choices) is
restricted: “I reduce my calls to the minimum. I only call when it is
necessary,” says O, a peasant. As for S, he adds: “I am more often called
than I make calls myself. In fact I rarely call and when I do so, it is almost
always to ring and hang out and have the person I am calling to call me
back.” Calls are not made on a regular basis: “It could go for days before I
call,” S says. The INS-PNUD survey notes that “The distribution of the
population of phone users by degree of use shows that 63% of them use
weakly that communication device, while only 37% report using it
frequently in their daily lives” (INS-PNUD 2009, p. 26). Therefore, having
a mobile phone does not mean that it is actually used or that it is used as
often as one would like. Those who are endowed with low economic capital
make calls less often, and when they do so, almost always they have to wait
to be called (being at the mercy of their interlocutors) (Alzouma, 2006,
2008; Donner, 2007). In rural areas, they are faced with a lack of electricity
and are obliged to resort to various “tricks,” such as the use of batteries to
recharge their phones (Alzouma, 2008). Their devices remain unused for
long hours or even for days. On average, poor households also have a lower
number of mobile phones per household than do high income households.
Consequently, more individuals in the same household must depend on
fewer phones.
Conclusion
As seen in this discussion, the digital divide cannot be solely reduced to
unequal access to computers or mobile phones. Even when most people do
have a mobile phone, social inequalities (including those inequalities
related to the use of that technology) are not suddenly erased by having
possession of the technical device. The physical availability of mobile
phones is just one dimension of the digital divide. Among many others are
also literacy, income, or even level of access and certain structural
constraints (location, availability of electricity, affording the calls) within
which the use of the technology takes place. Those structural constraints
do not affect all users the same way and to the same degree. Depending on
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Dimensions of the mobile divide in Niger 307
how they (the users) are economically, culturally or socially equipped (the
volume, structure and distribution of the capital they are endowed with
under its diverse forms) to face these constraints, their potential to benefit
from the use of technology may be different. Finally, it should be noted
that there is interplay between the economic capital, the cultural capital
and the social capital. Also, the factors associated with these different
forms of capital, namely the rural/urban divide, the differential access to
the Internet, and the disparity in cultural/technological competence, play
in ways that are so intricate that no statistical analysis or theoretical
rendition would be sound enough to capture all the complexity of their
interrelations.
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Vold Lexander, K. (2011). Names U ma puce: Multilingual texting in Senegal. Working
paper presented to the Media Anthropology e-seminar, European Association
of Social Anthropologists, 17–31 May 2011. Retrieved 21 October 2011 from
http://www.media-anthropology.net/file/lexander_multilingtext.pdf
Waverman, L., Meschi, M. and Fuss, M. (2005). The impact of telecoms on
economic growth in developing countries. Vodafone Policy Paper Series, No. 2,
March 2005. Retrieved 29 October 2011 from http://www.gsmworld.com/
documents/L_Waverman_Telecoms_Growth_in_Dev_Countries.pdf
Witte, J.C. and Mannon, S.E. (2010). The Internet and social inequalities. New York:
Routledge.
World Bank. (2009). Information and communication technologies for development 2009:
Extending reach and increasing impact. Washington DC: World Bank.
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Afterword
Internet freedom, nuanced digital
divides, and the Internet craftsman1
Sascha D. Meinrath
James Losey
Benjamin Lennett
New America Foundation, Open Technology Institute
The international consensus that communications is a fundamental
human right is emerging as we begin to understand the key role that the
Internet plays in numerous spheres of social life. In 2010, United Nations
Secretary-General, Ban Ki-moon, stressed the importance of access to the
Internet and information in his remarks to the General Assembly (United
Nations, 2010), and Spain and Finland have elevated broadband access to a
legal right (BBC, 2010; Morris, 2009). The economic and democratic
potential of Internet connectivity has driven 20 European Union nations
and the United States to set goals for universal broadband access (see
European Union, n.d.).
However, while most commentators and policy makers have focused on
the benefits of broadband and Internet connectivity, two significant
dilemmas receive less attention. First, the challenges faced by the
unconnected (the “Dark Side of Metcalfe’s Law” – see Tongia and Wilson,
2011) remain less explored. While the evolution of communications
technologies opens the door for greater equality (making information and
knowledge increasingly available to many), history demonstrates that
availability alone is insufficient. As telecommunications experts Rahul
Tongia and Ernest Wilson (2010) posit, “The more people included within
and enjoying the benefits of a network, the more the costs of exclusion
grow exponentially to the excluded.” A second oft-overlooked fact is that
all connectivity is not created equal; in the Internet age, which
technologies and devices you use to connect increasingly determine your
online opportunities. This differentiation is rapidly creating a more
nuanced digital divide that manifests itself, not just in terms of who has
access to broadband and who does not, but what users can actually do with
their connectivity.
These twenty-first century divides are driven by a worsening trend
among communication providers to increasingly lock down networks and
devices. The Internet, though predicated on an open, decentralized
architecture, is becoming increasingly subject to command-and-control
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310 Sascha D. Meinrath, James Losey and Benjamin Lennett
that limits how we communicate. In the coming years, how these new
divides are addressed will have far reaching implications that will either
fulfill the promise of the Internet as a universal and equal communications
medium, or serve to re-enforce existing societal inequities. By highlighting
the nuanced nature of today’s digital exclusion, this book has drawn
attention to new forms of discrimination and dis-empowerment that are
becoming hallmarks of the next generation of broadband networking.
These problems are surmountable, but only if we understand the nuances
and how to address them.
The digital divide has traditionally been defined as a “gap between
people with and without Internet access,” but DiMaggio et al. (2004) stress
the importance of the point that “understanding of digital inequality
requires placing Internet access in a broader theoretical context.” For
example, although the U.S. government claims that 95 percent of the
population has access to broadband, only 68 percent of all Americans, and
less than 50 percent of African-Americans and Hispanics actually use
broadband at home (Economics and Statistics Administration and
National Telecommunications and Information Administration, 2011).
The rural/urban divide is also quite pronounced, with home broadband
use at 60 percent in rural communities compared to 70 percent among
urban constituencies (ibid.).
Broadband adoption differentials around the globe parallel these
findings. The Organization for Economic Cooperation and Development’s
(OECD) broadband penetration rates (i.e., subscribers per 100
inhabitants) show Denmark leading OECD nations with a penetration rate
of 38 percent, followed closely by the Netherlands, Switzerland and Norway
(OECD, 2010). The U.S. is ranked fourteenth with a penetration rate of 27
percent (before Finland but lagging behind Germany, the U.K., Canada,
Sweden, France, and South Korea, among others) while the broadband
penetration in some OECD countries such as Mexico, Chile, and Turkey is
as low as 10 subscribers per 100 inhabitants (OECD, 2010). Globally, the
International Telecommunication Union estimates that home broadband
penetration rates range from 23 percent in the developed world versus 4
percent in developing countries (see Chart 1.4 in International
Telecommunications Union, 2010).
The stark difference between access and adoption is only part of a
considerably more complex digital divide ecosystem. A study by the
Investigative Reporting Workshop at American University found that the
best values for broadband were in the affluent areas while poorer areas
may pay slightly less, on average, for significantly slower broadband speeds
(Dunbar, 2011). This divide is even more pronounced when you factor in
the fact that actual broadband speeds may be only half of advertised
speeds (OfCom, 2011; Federal Communications Commission, 2010).
In addition, the network management practices used by many providers
can also inhibit digital freedoms for already disadvantaged communities.
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Afterword 311
In 2012 a joint study between the Body of European Regulators for
Electronic Communications and the Europe Commission (2012) found
widespread restrictions on wire-line and wireless broadband connections
including slowing speeds and setting data caps. Additionally, restrictions
on VoIP and peer-to-peer protocols impact one out of every five
subscribers.
These restrictive trends are enabled by several key technological
advances. For example, the IP Multimedia Subsystem (IMS), a still-evolving
technology primarily used on mobile networks (Waclawsky, 2005) allows a
provider to break the open Internet into a closed, small set of differentiated
services (e.g., email or voice traffic) and then charge for them on an
individual basis. Likewise, Deep Packet Inspection (DPI) technologies
allow a network operator to identify, monitor, and restrict access to specific
kinds of Internet applications and content. Providers are also interested in
using these same DPI technologies to track users and exploit user data for
targeted advertising (see Federal Trade Commission [2010, 2011]
regarding the “Matter of protecting consumer privacy in an era of rapid
change: A proposed framework for businesses and policy makers”).
Thus far, only the Dutch government has passed a network neutrality
law that would ban restrictive practices on both mobile and wire-line
networks (van Beijnum, 2012). Legal scholar, Tim Wu in a review of
information technologies of the past hundred years, finds that technology
has an unfortunate history of moving from open to closed (2010, p. 6).
This devolution poses significant dilemmas for closing the digital divide
by creating an unequal hierarchy of digital opportunities and new divides.
DiMaggio et al. stress that understanding the digital divide requires that
we fully understand the benefits a user is able glean though their
connectivity (2004). The closed mobile computing space foreshadowed by
Harvard Law Professor Jonathan Zittrain in 2008 is now a widespread
reality: from restrictions on tablets like the iPad to devices that resist user
modification or even render themselves inoperable if legal, though
unauthorized, software is detected on them (Lee, 2012; Meredith et al.,
2010).
Given current trends, those who can afford to access the Internet
through a higher speed or a more open wire-line connection will have
considerable advantages over users that can only afford more limited and
restricted wire-line or mobile connectivity. As providers further limit user
freedom, the promise of the Internet and broadband as a resource for
economic and societal empowerment, especially for society’s least
advantaged, will go unfulfilled.
New York University professor, Richard Sennett, posits that
craftsmanship, whether of a new cabinet or a new media, is a “basic human
impulse, the desire to do a job well for its own sake” (2008, p. 9). The ability
to localize, improve, question, and explore the tools we use is an important
facet of being human. Early Internet adopters, in addition to possessing
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312 Sascha D. Meinrath, James Losey and Benjamin Lennett
certain technical skills, were empowered to fundamentally shape the
medium, acting as Internet craftsmen to build, improve, and innovate the
technology.
As this volume documents, Internet service providers (ISPs) are moving
away from open and participatory architecture and systematically erasing
these freedoms and opportunities. Today, ISPs are focusing on locking
down every facet of their networks, designing systems that prioritize
consumption not creation, and creating barriers to user-driven
communications, adaptations, and innovations. Metcalfe’s law assumes
that a new network participant gains the benefits gleaned from the other
members of the network. As we are seeing today, however, companies are
garnering enormous profits by commoditizing every form of
communications possible and the inefficiencies caused by these practices
(in terms of lowered information flow, network congestion at centralized
monitoring points, greatly decreased innovation at the edges of the
network, etc.) are coming at the literal expense of edge users.
However, technologies exist today that would dramatically lower the
cost of communications, increase adoption rates, fuel the development of
new services and applications, and are synergistic with pre-existing
infrastructure. Digital justice advocates should be aware of these emerging
technologies and actively support their development and adoption.
Using off-the-shelf Wi-Fi routers with upgraded software, mesh
networking facilitates local-to-local communications, allowing individuals
to stream video, share local media, and use VoIP for free telephone calls
(Meinrath and Pickard, 2009). Current implementations range from
covering a few blocks in Detroit, Michigan (Breitbart and Chodoroff,
2010) to covering hundreds of square kilometers in Vienna, Austria
(Forlano et al., 2011). The impacts from these networks can be quite
extraordinary: “[In] Berlin, a city that has struggled with depopulation,
high unemployment and budget deficits since the fall of the Berlin Wall,
the community wireless network Freifunk has provided free Internet
access to residents who cannot afford commercial services since 2002”
(Forlano et al., 2011).
Peer-to-peer networking on mobile handsets creates additional
opportunities for edge-user empowerment. In Australia, the Serval Project
(see http://www.servalproject.org) has developed mesh networking for cell
phones running the Android operating system. Their system allows users
to make free voice calls through a local network or, by adding Asterisk or
another VoIP gateway, to almost anywhere in the world (Johnston, 2011).
Gnu Radio and the OpenBTS projects are developing alternatives to
local mobile networks. OpenBTS created an open-source GSM air
interface, enabling users to build their own cell phone networks and
provide low-cost or free services (Burgess, 2010). Gnu Radio, a software
development toolkit that performs signal processing and permits users to
develop software radios using cheap hardware, could put these adaptive
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Afterword 313
networking technologies into the hands of the masses (see http://
gnuradio.org/redmine/wiki/gnuradio). Many of these projects are
currently collaborating on the development of the Commotion Wireless
Project, a free “open-source communication tool that uses mobile phones,
computers, and other wireless devices to create decentralized mesh
networks” (Commotion Wireless, n.d.).
Yet the trajectory of regulation prevents the implementation of these
innovations. For example, spectrum reforms to allow widespread use of
cognitive radio technologies (especially shared and opportunistic
spectrum access) have been met with hostility by regulators and incumbent
telecommunications companies worldwide. Instead, the overarching focus
has been on maintaining artificial scarcity through an almost singular
focus on spectrum auctions and granting exclusive licenses to a small
group of providers. However, as smart radio technologies mature, the gap
between technological capabilities and permissible use will increase – a
process that will eventually lead to the rise of a generation of
“electromagnetic jaywalkers.”
Bridging today’s digital divides means reforming policies and
regulations, but also understanding that Internet craftsmen are digital
literacy crusaders that bring new thinking and innovative technologies to
the fore. Bridging the digital divide means getting rid of antiquated
barriers that prevent the Internet craftsmen and local communities from
implementing outside-the-box thinking, but it also means making it illegal
to develop new barriers that prevent tinkering and innovations at the edge
of the network. Eliminating twenty-first century digital divides means
providing the resources and opportunity necessary for anyone to develop
innovative infrastructure, new services and applications, and
improvements to communications that better meet their own needs and
those of their communities. This is the challenge that the next generations
of digital justice advocates face and must overcome.
References
BBC. (2010, July 1). Finland makes broadband a “legal right.” BBC, Online at:
www.bbc.co.uk/news/10461048.
Body of European Regulators for Electronic Communications. (2012, May 29). A view
of traffic management and other practices resulting in restrictions to the open
Internet in Europe. Online at: https://ec.europa.eu/digital-agenda/sites/digitalagenda/files/Traffic%20Management%20Investigation%20BEREC_2.pdf
Breitbart, J. and Chodoroff, B. (2010, August) Community wireless mesh prototype
in Detroit, MI, U.S. Online at: http://www.newamerica.net/node/34925
Burgess, D.A. (2010, September 25). The man burns in 341 days. The OpenBTS
Chronicles. Online at: http://openbts.blogspot.com/2010/09/man-burns-in341-days.html
Commotion Wireless (n.d.). Home. Accessed 2012, October 31. Online at: https://
commotionwireless.net/
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314 Sascha D. Meinrath, James Losey and Benjamin Lennett
Dunbar, J. (2011, February 28). Wealthy suburbs get best broadband deals: D.C.,
rural areas lag behind. Washington, DC: Investigative Reporting Workshop.
Online
at:
http://investigativereportingworkshop.org/connected/story/
washington-dc-broadband-speed/
DiMaggio, P., Hargittai, E., Celeste, C. and Shafer, S. (2004). From unequal access
to differentiated use: A literature review and agenda for research on the digital
divide. In K. Neckerman (ed.). Social Inequality. New York: Russell Sage
Foundation, 355–400.
Economics and Statistics Administration and National Telecommunications and
Information Administration. (2011). Exploring the digital nation. Washington,
DC: NTIA. Online at: http://www.ntia.doc.gov/files/ntia/publications/
exploring_the_digital_nation_computer_and_internet _use_at _home_
11092011.pdf
European Union. (n.d.). Annex 2 – Key targets of national member states
broadband strategies. Online at: https://ec.europa.eu/information_society/
activities/broadband/docs/annex_2.pdf
Federal Communications Commission. (2010, August). FCC broadband
performance OBI technical paper, no. 4. Online at: www.fcc.gov/Daily_
Releases/Daily_Business/2010/db0813/DOC-300902A1.pdf
Federal Trade Commission. (2010, February 28). Comments of AT&T Inc. Online
at: www.ftc.gov/os/comments/privacyreportframework/00420-58059.pdf
Federal Trade Commission. (2011, February 18). Comments of Verizon and Verizon
Wireless. Online at: www.ftc.gov/os/comments/privacyreportframework/0042858044.pdf
Forlano, L., Powell, A., Shaffer, G. and Lennett, B. (2011, February). From the
digital divide to digital excellence: Global best practices to aid development of
municipal and community wireless networks in the United States. Online at:
http://www.newamerica.net/publications/policy/from_the_digital_divide_to_
digital_excellence
International Telecommunications Union. (2010). Measuring the information
society 2010. Geneva: International Telecommunications Union. Online at:
http://www.itu.int/ITU-D/ict/publications/idi/material/2010/MIS_2010_
without_annex_4-e.pdf
Johnston, C. (2011, January 31). Researchers enable mesh WiFi networking for
Android smartphones. Ars Technica. Online at: http://arstechnica.com/
gadgets/news/2011/01/researchers-enable-mesh-wifi-networking-for-androidsmartphones.ars
Lee, T.B. (2012, October 26). Jailbreaking now legal under DMCA for
smartphones, but not tablets. Online at: http://arstechnica.com/techpolicy/2012/10/jailbreaking-now-legal-under-dmca-for-smartphones-but-nottablets/
Meinrath, S. and Pickard, V. (2009). The rise of the Intranet Era: Media, research
and policy in an age of communications revolution. In K. Howley (ed.).
Globalization and communicative democracy: Community media in the 21st century.
London: Sage Publications. Online at: http://www.newamerica.net/
publications/policy/rise_intranet_era
Meredith, D., King, J., Meinrath, S. and Losey, J. (2010, October 13). Mobile
devices are increasingly locked down and controlled by the carriers.
Washington, DC: New America Foundation, Open Technology Initiative.
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Afterword 315
Online at: http://oti.newamerica.net/blogposts/2010/mobile_devices_are_
increasingly_locked_down_and_controlled_by_the_carriers-38418
Morris, S. (2009, November 17). Spain govt to guarantee legal right to broadband.
Online
at:
http://www.reuters.com/article/2009/11/17/spain-telecomsidUSLH61554320091117
OECD. (2010, June). Broadband statistics, 1d(3), fixed broadband subscriptions
per 100 inhabitants, by technology. Online at: http://www.oecd.org/
dataoecd/21/35/39574709.xls
OfCom. (2011, March 2). Average speed is still less than half advertised speed.
Press release. Online at: www.media.ofcom.org.uk/2011/03/02/averagebroadband-speed-is-still-less-than-half-advertised-speed/
Sennett, R. (2008). The craftsman. New Haven, CT, U.S.: Yale University Press.
Tongia, R. and Wilson III, E.J. (2010, March). The dark side of Metcalfe’s Law:
Multiple and growing costs of network exclusion. Presented at Beyond
Broadband Access Workshop, Washington, DC. Online at: http://www.cstep.
in/docs/Network%20Exclusion%209-22-09.pdf
Tongia, R. and Wilson, E.J. III. (2011). The flip side of Metcalfe’s Law: Multiple
and growing costs of network exclusion. International Journal of Communication 5,
665–681.
United Nations. (2010, May). Governments must stand up for press freedom. Press
release. Online at: http://www.un.org/News/Press/docs/2010/obv875.doc.htm
van Beijnum, I. (2012, May 10). Netherlands becomes world’s second “net
neutrality” country. Online at: www.arstechnica.com/tech-policy/2012/05/
netherlands-becomes-worlds-second-net-neutrality-country/
Waclawsky, J.G. (2005). IMS: A critique of the grand plan. Business Communications
Review, 35(Oct.), 54–55.
Wu, T. (2010). The master switch. New York: Random House.
Note
1 Adapted from A growing digital divide by Meinrath, Losey, and Lennett. IEEE
Internet Computing. July/August 2011.
The Digital Divide_BOOK.indb 315
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Index
Locators in bold refer to figures/tables
abilities 241; see also skill sets (digital)
academic community: see higher
education
access, computer/internet 18, 24,
110–11, 115; Asia 150–4, 161–2,
271–8, 272–5, 285–94, 286; benefits
of 62–4, 113; Central and Eastern
Europe 189; Egypt 211–12; Estonia
196–8; global distribution 147;
importance of 45–7, 46–7; Israel
223–4; Japan 88–90, 89–90; mobile
89; physical and material 37–40, 39;
research questions 57–8, 62–4; role
in Arab Spring 214–16, 216; Russia
119, 120, 122–3, 124–8, 125, 127;
South Eastern Europe 170–2; see also
first order digital divide;
motivation; usage, computer/
internet
accessing ability 241
activism, online: see cyber activism
activities, online: see entertainment
applications; serious applications
adolescents 179–90
adoption (new technology) 58, 91;
attitudes 226–7; broadband 85–91,
101–2, 310; China/Taiwan/Hong
Kong 151–4; European Union (EU)
64; resources and appropriation
theory 32–40; S-curve 38–40
advancement, technological: see
development, technological
Afghanistan 274, 276, 278
Africa: see Niger
age 42, 44–5; Central and Eastern
Europe 184, 186–7; China/Taiwan/
Hong Kong 155–7, 161–2; Estonia
195, 200–1; Iran 245; Middle
The Digital Divide_BOOK.indb 316
Eastern populations 215; Russia
126–8, 129; Taiwan 155; United
States 81
agency 201–3
agreeableness 37
alienation 3, 20, 124
alternatives to the internet 45
America, North: see United States
American Life Project 43, 71–82
analytical models 184
analyzing ability 241
anxiety 37, 226–7
appropriation (theoretical
frameworks) 32, 32–5, 34, 112
Arab Spring 8, 209–19, 216
Arabia 8
arithmetic 238
articulation, double 17
Asia 150–4, 271–8, 272–5, 285–94,
286; see also Central Asia; China;
Hong Kong; India; Taiwan
attitudes 55, 184, 226–7, 231
auction services 95–8
Australia 88, 90
Austria 88, 90
authoritarian regimes 212; see also
censorship, internet
Bahrain 216–17
Balkans 167–77
Bangkok (Thailand) 287–9
BCG e-Intensity Index 119
Belgium 88, 90
Big Five (personality dimensions) 37
Blogger 217
Bourdieu, Pierre 55, 194, 298–9, 302
Brahmins 140
Brazil 6, 107–15; see also Latin America
5/8/2013 2:33:20 PM
Index 317
BRIC (Brazil, Russia, India and China)
6; see also individual countries
respectively
broadband: adoption 85–91, 101–2,
310; applications 95–6, 96–9;
definition 91
Bulgaria 7, 179–90, 188
Cairo 209–11, 213, 217
Canada 88, 90
capital: economic 134, 299; social
17–19, 22–3, 70–1, 79–82, 80–1, 115
capital, cultural: see cultural capital
capitalism 17, 21–6, 147–8, 194
caste system 136–9
Castells, M. 18, 68–9
categorical inequality 29–35, 32
causality 184
cell phones 300, 302–6, 312–13
censorship, internet 159–60, 311;
Central Asia 278–81, 279; China
217–18; Egypt 216–17; Middle East
216–18; see also liberalization
Central and Eastern Europe 179–90
Central Asia 270–1, 281–2; censorship
278–81, 279; infrastructure and
policies 271–5, 272–5; netizens
275–8, 276
chances, life: see life chances
change, socio-cultural 19–20
childcare 291–4
Chile 88, 90
China 7, 147–50, 159–60; first order
digital divide 153; internet
censorship 217–18; trends in digital
access 152, 161–2
class 3, 20; Brazil 108; caste system
(India) 136–9; Estonia 194–5; Max
Weber 168–9; Russia 118; United
States 68, 224–5
coherence, social 4
Coleman, J. 70
collaboration, online 167–8, 172–7; see
also cyber activism
communal action: see Gemeinschaft
communication skills 41
Communism 7–8, 193–5, 223; Central
Asia 270–1, 281–2; see also Estonia
competencies 241; see also skill sets
(digital)
computer science 172; see also science
and engineering
confidence 183–90
The Digital Divide_BOOK.indb 317
configuration 17–26
conflict perspectives 134–5, 182, 184,
224–5, 229
connection speed (internet) 60, 272–5,
276, 310–11; see also broadband
conscientiousness 37
consumerism 21, 195
consumption 21, 68, 92–3, 95, 121, 129;
conspicuous 305; Estonia 195;
habitus 226; India 137, 142–3;
prioritization of 312
content-creation skills 41
content-related skills 40–1, 41
craftsmanship 311–12
creating ability 241
cultural capital 18; Brazil 134–5;
broadband use 90–1, 93–4, 96, 99,
101–2; Israel 225–6; Niger 299,
302–6
cultural perspectives 137, 196–7, 225–7,
229–34
cultural transition: see transition,
socio-cultural
cyber activism: Arab Spring 209–19;
Central Asia 278–81, 279
cyber cafés 277, 285–94, 286
cycle, product 110
Czech Republic 88, 90
daily internet usage 242–3, 243, 245–6
data sources 6–10; Brazil 110–11;
reliability 43; South Eastern Europe
170–2
democratization 85, 114–15; Middle
East 212; Niger 305
demographics: Arab Spring 214;
Central Asia 275–8, 276; theoretical
frameworks 29
Denmark 88, 90
dependency 22
development, technological 18–19,
22–3, 148, 267–8; Africa 297–300,
312; e-social development 115; Far
East 161–2; modernizationism 271;
NGOs 279; scholarship 237;
subjective poverty 113; United States
67, 224
diachronicity 110
differentiation 309; Central and
Eastern Europe 180–4, 188–90;
emerging digital differentiation
179–84; Estonia 194–5, 204;
theoretical frameworks 19–20, 26, 31
5/8/2013 2:33:20 PM
318 Index
diffusion of technology 35, 39, 55–6,
110; Central Asia 270–1; Latin
America 254–6; normalization vs.
stratification models of 38, 148–50
digibetism 196
digital divide: first order 150–4, 153 see
also access; second order 154–7, 156,
179–90 see also usage; three-tiered
model 238
digital era: see information age
digital inequality: see inequality
digital literacy: see media literacy; skill
sets
digital natives 180
digital skills: see skill sets
digital stratification: see stratification
digital technology: see information
technology
digital usage: see usage, computer/
internet
disintegration: see integration
dissemination of internet technology:
see access; diffusion of technology
distance, social 114–15
division of labor 130–1; Durkheim,
Emile 4, 108, 118; functionalism 92,
210; Weber, Max 20
The Division of Labor in Society
(Durkheim) 118
domestic use of ICT: see home use of
ICT
double articulation 17
doxa 226
drop-outs: college 141; internet users
36
Durable Inequality 30–1
Durkheim, Emile 1, 4, 20; cyber
activism 210, 218; Latin America
108, 253–6, 267–8; Niger 298–9;
Russia 130
early adopters 30
Eastern Europe 7–8; Central and
Eastern Europe 179–90; South
Eastern Europe/Balkans 167–77
economic capital 134, 299
economic transition: see transition,
socio-cultural
education 42, 44–5, 47, 172; broadband
use 99; Central and Eastern Europe
184, 186–7, 189; China/Taiwan/
Hong Kong 161–2; e-learning 96,
171; higher 72–4, 172–6, 237–47;
The Digital Divide_BOOK.indb 318
India 141; Iran (University of
Tehran) 237–47; Israel 229; Middle
East 215; social policies 113–14;
South Eastern Europe 172–6;
United States 72–5, 76, 81; see also
students
e-economy 21, 45
effects focus, internet research 62–4
Egypt 8, 211–14, 216, 216–17
e-learning 96, 171
elite, information 5, 48
e-literacy: see skill sets (digital)
e-mail 36, 45, 120, 121, 232, 233, 288
emerging digital differentiation
179–84
emerging economies 6–7
employee referral programs 142
enablement 119
engagement 119
Engels, Friedrich 20
engineering: see science and
engineering
entertainment applications 44, 92–9,
121, 182, 199, 260–1
entrance exams 141–2
environment, information 199–204
equality: definition (internet access)
118–19; relationship to national
prosperity 216; see also inequality
e-social development 115
Estonia 7–8, 88, 90, 193–204
ethnicity 31, 76, 81, 270; Estonia 195–7,
198; Israel 222–34, 229–30; United
States 224–5
EU Kids Online 180
EU27 59
Eurobarometer surveys 59, 59–60
European Union (EU) 6, 38, 55–64,
57, 59, 61; see also Eastern Europe
evaluating ability 241
exclusion: see inclusion/exclusion
extraversion 37
Far East: see China; Hong Kong;
Taiwan
feminism 270
fiction 95–6
Finland 88, 90
first order digital divide 149–50,
150–4, 153; see also access,
computer/internet
flows, information 17–18, 312
formal skills 41
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France 88, 90
free will 201–3
frequency (internet use) 128–30,
198–204, 265–8, 301
FSU (former Soviet Union) 7–8, 193–5,
223
functionalism 92, 118, 210–11, 218–19
gaming 44, 155; Singapore and Taiwan
292–3; Thailand 287
gaps: knowledge 44, 64, 91, 172–7; sex/
gender 90, 126; usage 43–5, 154, 157;
see also digital divide; sex/gender
Geiger, Theodor 55
Gemeinschaft 169, 173
gender: see sex/gender
gender gap: see under gaps
gender regime 199–200
generalizations 130
Germany 6, 56, 88, 90, 312
gerontocracy 195
ghettos 24
Gini coefficient 216
global informational capitalism 17,
21–6, 147–8, 194
Greece 88, 90
habitus 55, 194, 226, 312; see also
attitudes
Hargittai, Eszter 42, 61–2, 128, 173–4
health services 63, 95–6
higher education 72–4; South Eastern
Europe 172–6; University of Tehran
237–47
highly developed countries 6
Hinduism 140
Holland 35–7, 42–7, 182, 311
home use of ICT 310; Brazil 110–11;
Central and Eastern Europe 182,
186–7; Central Asia 277; European
Union 58–60; Israel 225, 229–30;
Latin America 256, 258–61, 265,
268; Russia 123
Hong Kong 7, 147–50, 158–9; first
order digital divide 153; second
order digital divide 156; trends in
digital access 151–2, 161–2
Household Download Index 119
household income: see income
Hungary 7, 88, 90, 179–90, 188–9
Iceland 88, 90
ICT industry (India) 138–9
The Digital Divide_BOOK.indb 319
illegal immigrants 109
illiteracy 109
immigrants 222–3, 228–34, 229–31,
233
inclusion/exclusion 23, 26, 47–9, 48;
BRIC (Brazil, Russia, India and
China) 6, 115; China/Taiwan/Hong
Kong 159; India 140–2; United
States 69
income 72–5, 76, 81, 99; China/
Taiwan/Hong Kong 161–2;
diffusion of technology 110; Russia
124–6
India 7, 134–43
individualism 20–3, 25–6, 29, 124
inequality 17–26, 34; categorical
29–35, 32; durable 30–1; Middle
East 213–14; network society 47–9,
48; opportunities and outcomes
118–21; relational 29–32;
relationship to national prosperity
216; see also positional inequalities
information age 17, 21–3, 26
information elite 5, 48
information environment 199–204
information flows 17–18, 312
information skills 41
information society 21–3; continuum
vs. two-tiered model 31–2;
Eurobarometer surveys 59, 59–60;
privilege/disadvantage 159–60
information technology 17–22, 35;
alternatives to the internet 45;
industry in India 138–9; integration
in Latin America 256–62, 257–61;
mobile phones 300, 302–6, 312–13;
social shaping of 19–20, 85
informational capitalism 17, 21–3, 26,
148
informationalism 148
integration (social): Durkheimian
paradigm 253–6, 266–8; Estonia
197, 200; Latin America 262, 265
integration of internet technology:
Central and Eastern Europe 182;
European Union 62–3; Latin
America 256–62, 257–61
intensity (internet use) 128–30,
198–204, 265–8, 301
inter-generational digital transfer
172–6, 184, 190
International Telecommunication
Union (ITU) 147
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320 Index
The Internet and Social Inequalities (Witte
& Mannon) 210
internet access: see access, computer/
internet
internet cafés (ICs) 277, 285–94, 286
internet censorship: see censorship,
internet
internet competence: see skill sets
(digital)
internet content 41
internet effects research 62–4
internet penetration: see access,
computer/internet
internet skills: see skill sets (digital)
internet use: see usage, computer/
internet
internet users/non-users 88; Central
Asia 275–8, 276; Estonia 197–8, 198;
European Union 59–63;
Netherlands 46; Russia 126–8; sex/
gender of 90, 126; skilled vs
non-skilled 247, 277; United States
67–8, 75–82, 76–82
internetization 193
interpersonal relationships 17–19, 115,
174; see also social media
interregional differences in internet
coverage (Russia) 123
Iran 8–9, 237–47
Ireland 88, 90
Israel 8, 88, 90, 222–4, 232–4; conflict
perspectives 224–5; cultural
perspectives 225–6; data and results
228–32, 229–32
Italy 88, 90
Japan 6; broadband availability 88–90,
89–90; broadband policy
development 86, 86–7; cultural
capital 90–1; growth of broadband
applications 86–7, 87–8
job hunting 45, 290
Kazakhstan 272, 274–6, 277
knowledge gap 44, 64, 91, 172–7
Korea 88, 90
Kyrgyzstan 272, 272–5, 274, 276, 278
labor, division of: see division of labor
language barrier 142, 287–9
Latin America 253, 268–9;
dissemination of internet
technology 254–6; internet
The Digital Divide_BOOK.indb 320
integration 256–62, 257–61; role of
the State 262–8, 263–4, 266; see also
Brazil
liberalization 7, 195, 212, 217; see also
censorship, internet
Lievrouw, Leah 199
life chances 20–1, 24–6; cultural
perspectives 68–9; role of the State
109–15
lifestyles 37, 75–9, 93, 134–8, 226,
304–6; see also doxa; habitus
literacy 109, 302–4; India 136–7; Iran
238; media 40, 239–41; Middle East
213, 216; see also new literacies
literacy, digital: see digital literacy
Luxembourg 88, 90
Mannon, S. E. 5, 71–2, 137, 148, 193,
202, 210, 215, 224–6, 297–8, 302
marriage 139
Marx, Karl 1–3; Brazil 107–8; Central
Asia 270; China/Hong Kong/
Taiwan 147–8; Niger 298–9; Russia
130
material access 40
Matthew effect 149, 154, 184, 187–9
MDCs (more developed countries) 6
media literacy 40, 239–41
medical services 63, 95–6
medium-related skills 40–1, 41
mentality 55, 184, 226–7, 231
methodology 29, 42; Central and
Eastern Europe 185; Iran 240–2;
Israel 228; Japan 94–6; Russia 128,
130; South Eastern Europe 170
Metro Manila (Phillipines) 289–91
Mexico 88, 90
Middle East 8–9, 212–14, 218–19; see
also Afghanistan
migrants 291–4; see also immigrants
minority groups 227; Central Asia 278;
Estonia 195–7, 198, 200; Israel
222–34; Middle East 215–16; see also
ethnicity
mobile internet access 297–8, 312;
Brazil 111; India 135; Israel 224;
Japan 89; Niger 300, 305–6; Russia
120
mobile phones 300, 302–6, 312–13
mobility, social 22–3; see also social
capital
models: analytical 184; normalization vs.
stratification 38, 148–50; path 187
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Index 321
modernization theory 210
Mongolia 272, 274, 275, 276
monthly internet audience in Russia
119–20
more developed countries (MDCs) 6
Mosco, Vincent 3
motivation 35–7, 91, 101, 226–7
Mubarak, Hosni 209, 211
multicollinearity 185, 228
multi-dimensional approach 18–19,
23–5, 196–7
multimedia literacy 40, 239–41
music downloads 45, 93–9, 95–6, 260–1
Nadwas, Tweet 209
natives, digital 180
neo-functionalism 118; see also
functionalism
neo-liberalism 22; Egypt 209–10; Niger
273; see also global informational
capitalism
net-evaders 36
Netherlands 35–7, 42–7, 88, 90, 182,
311
netizens: see internet users/non-users
network theory 39
networked individualism 22–3
networked society 21–3, 47–9, 48, 69
neuroticism 37
New Left 130
new literacies 167–8, 175; see also skill
sets (digital)
New Zealand 88, 90
news services 45, 77–9, 79
Niger 297–307; internet access 300–6;
theoretical frameworks 298–9
Norris, Pippa 213–14
North America: see United States
Norway 88, 90
numeracy 238
occupation 47; Asia 291; India 134–43;
Israel 229–32; Russia 126–8, 127
occupational prestige: see prestige
OECD (Organization for Economic
Cooperation and Development) 7,
87, 88–90, 263–4, 266, 310; see also
PISA (Programme for International
Student Assessment)
OFW (overseas filipino worker) 291–2
omnivorous use 93–4
online activities: see entertainment
applications; serious applications
The Digital Divide_BOOK.indb 321
online collaboration 167–8, 172–7; see
also cyber activism
online competencies: see skill sets
(digital)
online public sphere 8, 19, 26, 167,
173–4; see also social media; social
networks
online skills: see skill sets (digital)
open category (OC) 136–7
openness 37
operational skills 41
opportunities 118–21
Organization for Economic
Cooperation and Development
(OECD) 7, 87, 88–90, 263–4, 266,
310; see also PISA (Programme for
International Student Assessment)
other backward classes (OBCs) 136–7
outcomes 118–21
overseas filipino worker (OFW) 291–2
parental background/education
183–4, 184
participating ability 241
participation: see inclusion/exclusion
path models 184
patriarchy 271
patterns, consumption: see
consumption
peer-to-peer networks 312
penetration of information
technologies: see access, computer/
internet
performance tests (digital skills) 41–3
personal inequalities 33
personality characteristics 37
perspectives: conflict 134–5, 182, 184,
224–5, 229; cultural 137, 196–7,
225–7, 229–34; functionalist 92,
118, 210–11, 218–19
Pew Internet and American Life
Project 43
Philipines 289, 289–91, 291
physical access 37–40
PISA (Programme for International
Student Assessment) 253, 260–7
Poland 7, 88, 90, 179–90, 189
political alleigances 108
political engagement 21, 85, 209–19,
278–81, 279
political measures to address
inequality: Brazil 112–14; European
Union 56–7, 57; India 143; Latin
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322 Index
America 262–8, 263–4, 266; South
Eastern Europe 177
Portugal 88, 90
positional inequalities 33; European
Union (EU) 62; United States 72–5
post-Fordist welfare 23–4
post-socialist transition: see
Communism; Estonia
poverty 22, 272, 304–6
power 3–5, 17–25, 30–2, 92, 169;
Central Asia 282; conflict
perspectives 224; state 219
prestige 3–4, 291; cultural perspectives
225–7; India 137; Israel 225–32;
South Eastern Europe 169; see also
social/socioeconomic status
private use of ICT 186–7
privilege 218; Brazil 114; Central and
Eastern Europe 185–8; Estonia
194–6; European Union 56, 62–4;
Far East 148, 158–60; India 136–42;
Latin America 258–65; Middle East
8; Russia 130; United States 215
product cycle 110
production, relations of 17–19, 24–5
professors 174–5
Programme for International Student
Assessment (PISA) 253, 260–7
programming 41, 175
The Protestant Ethic and the Spirit of
Capitalism (Weber) 69
public policy: see political measures to
address inequality
public sphere, online 8, 19, 26, 167,
173–4; see also social media; social
networks
purposes of internet use: see
entertainment applications; serious
applications
Putnam, R. 70
Qatar 216
questionnaires 46, 227, 240–2
race: see ethnicity
referral, employee 142
regime, gender 199–200
regulation: see political measures to
address inequality; state, role of
relational inequality 29–32
relations of production 17–19, 24–5
relationships, social 17–19, 70, 115, 174;
see also social media
The Digital Divide_BOOK.indb 322
research questions 57, 57–64, 149
residential segregation 223
resources (theoretical frameworks) 32,
32–5, 34
‘rich get richer’ 149, 154, 184, 187–9
The Rise of the Network Society: The
Information Age: Economy, Society, and
Culture Volume I (Castells) 68–9
Romania 7, 179–90, 188
rural areas: Brazil 110–11; Niger 301–2,
305–6; Russia 129; Taiwan 151;
United States 75, 77
Rusia Longitudinal Monitoring Survey
(RLMS) 126
Russia 6, 118–31, 193–5
Russian Federal State Statistics Service
Household Budget Survey 6, 118
safety skills 183
satellite internet 272–3
saturation (diffusion of ICT) 38–9;
European Union (EU) 56; Taiwan
149, 151
Saudi Arabia 216, 217–18
scheduled castes (SCs) 136–42
scheduled tribes (STs) 136–42
scholarship 1–5, 57, 130, 149, 310
schools 125; Asia 151–2, 161; Brazil
111–14; India 136, 142; see also
higher education
science and engineering 141–3, 172
S-curve (adoption) 38–40
second order digital divide 149–50,
154–7, 156, 179–90, 237–47; see also
usage, computer/internet
second world 7–8, 193–5, 223, 270–1,
281–2
Second World War 21–2
SEE (South Eastern Europe) 167–77
segregation 223
self-confidence 183–90
self-efficacy 242–7
Serbia 7, 167–77
serious applications 44–5, 92–3, 121,
182, 199
sex/gender 30–1, 45, 75, 81; broadband
applications 95–6, 96–9; Central
and Eastern Europe 184, 186–7;
Central Asia 278; China/Taiwan/
Hong Kong 152–3; Estonia 195, 199;
Iran 244–5; Middle East 213; Russia
126–8; Western Society 227
shopping 95–6, 99
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Singapore 291, 291–4
skill sets (digital) 18, 60–1, 61; content
and medium related 41; Iran 238–9,
244, 245–7; performance tests 40–3;
Philippines 289–91; safety 183;
South Eastern Europe 171; see also
literacy
skilled users 247, 277
Slovak Republic 88, 90
Slovenia 88, 90
SME (social media and entertainment
related internet use) 200–3, 200–4;
see also entertainment applications
SNS site 200, 233; see also social media
social capital 17–19, 22–3, 70–1, 79–82,
80–1, 115
social class: see class
social coherence 4
social distance 114–15
social inequality: see inequality
social media: Arab Spring 209–19; and
entertainment related internet use
200–3, 200–4; South Eastern
Europe 167–77
social mobility 22–3
social networking sites (SNS) 200, 233
social networks 17–19, 18, 115, 174
social participation: see inclusion/
exclusion
social policies: see political measures to
address inequality; state, role of
social relationships 17–19, 70, 115, 174;
see also social media
social shaping of technology 19–20, 85
social stratification: see stratification
sociality 168–9, 177
social/socioeconomic status 62, 92;
Estonia 194–202; Israel 227; Max
Weber 108, 291; see also prestige
socio-cultural change 19–20
sources, data: see data sources
South Eastern Europe (SEE) 167–77
Spain 88, 90
Stände 168–9, 176
state, role of: Brazil 110, 112–14; Latin
America 262–8, 263–4, 266; state
owned broadcasters 212; welfare
21–5
statistics: data sources 6–10; reliability
43
status, social: see social/socioeconomic
status
Steinert, H. 23–4
The Digital Divide_BOOK.indb 323
strategic skills 41
stratification 1–3, 7–11, 86, 92; Central
and Eastern Europe 182; classical/
Weberian theory 68, 107–9, 130,
167–8, 172–7; diffusion of
technology 38; Estonia 193–204;
India 136, 140; internet effects
research 62–4; Iran 246–7; neofunctionalism 118; role of the State
112–14; social status 291–3; United
States 67
stress 37
students: Central and Eastern Europe
179–90; Latin America 262–7; SEE
(South Eastern Europe) 172–6;
University of Tehran 237–47
surveillance 24
surveys 227, 240–2
Sweden 88, 90
Switzerland 88, 90
symbolic capital: see cultural capital
Syria 216, 217–18
Taipei (Taiwan) 291–3
Taiwan 7, 147–50, 291, 291–4; internet
access and activities 158, 161–2;
second/first order digital divide
153, 156; trends in digital access
151
Tajikistan 272, 275, 276, 277
teaching professionals 174–5
technological development: see
development, technological
technology, digital/information 17–22,
35
technophobia 37, 226–7
telematics 109
telephones, mobile 300, 302–6, 312–13
Thailand 287–9
theoretical frameworks 1–5, 17–26,
298–9; appropriation and resources
32–5, 34; BRIC countries 107–15;
conflict perspectives 134–5, 182,
184, 224–5, 229; cultural
perspectives 137, 196–7, 225–7,
229–34; functionalism 92, 118,
210–11, 218–19; generalizations 130;
internet effects research 62–4; Iran
239–40; modernization theory 210;
network theory 39; relational
inequality 29–32; Weberian 168–9
thief nets 214
3G 135
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324 Index
three-tiered model 238
Tilly, Charles 30–1
tipping point 38–9, 39
training: see education
transition, socio-cultural 19–20, 22–3,
167–77, 193–204, 294
tribes, scheduled (STs) 136–42
Tunisia 212, 216, 217–18
Turkey 88, 90
Turkmenistan 272, 274, 276
Tweet Nadwas 209
21st century literacies: see skill sets
(digital)
Twitterati 209
UCLA Internet Reports 43
unemployment rate: Estonia 195–6;
Germany 312
United Arab Emirates 216
United Kingdom 88, 90
United States 38, 67–8, 88, 90;
community types 75–9, 76–9;
comparison with Estonia 204;
cultural perspectives 68–9;
education and income 72–4, 72–5,
81; internet and social capital 70–1,
79–82, 80–1
urban areas 77, 110–11, 135; Niger
301–2; Russia 129; Taiwan 151
usage, computer/internet 43–5,
58–60, 59, 75–82, 78, 80–1;
broadband 92–4; China/Taiwan/
Hong Kong 154–7; Estonia 198,
198–204, 200–3; gap 43–5, 154,
157; at home 58–60, 110–11, 123,
182, 186–7, 225, 229–30, 256; Iran
The Digital Divide_BOOK.indb 324
242–3, 243; private use 186–7;
Russia 119, 120; see also access,
computer/internet; home use of
ICT; intensity (internet use);
second order digital divide;
versatility (internet use)
USSR 193–5; see also Russia
Uzbekistan 272, 276, 277
values: see lifestyles
van Deursen, A. 40–4
van Dijk, J. 5, 42–4
versatility (internet use) 198–204
Weber, Max 1, 3–4, 20; Brazil 108;
Estonia 194; India 134–5; Israel 225;
Niger 298–9; Russia 130; South
Eastern Europe 167–9; stratification
theory 167–8, 172–7
welfare, state 21–5
WI (work and information related
internet use) 200–3, 200–4; see also
serious applications
wireless 312
Witte, J. C. 5–6, 71–2, 137, 148, 193,
202, 210, 215, 224–6, 297–8, 302
word of mouth 77
World War II 21–2
Yemen 216
youth 195; adolescents 179–90; Latin
America 258–61, 258–67; Middle
East 215; see also students
zero-inflated Poisson (ZIP) model
99–100, 100
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